ISSN 2304-7712 (Print) International Journal of Advanced … 5 No 1.pdf · 2016. 4. 30. · 3 reducing the dimensional dependence for rank-based similarity search jeevan arjun shelke,

VOLUME 5 NUMBER 1 May 2016

International Journal of Advanced

Engineering and Science

ISSN 2304-7712 (Print)

ISSN 2304-7720 (Online)

International Journal of Advanced Engineering and Science, Vol. 5, No.1, 2016

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International Journal of Advanced Engineering and Science

ABOUT JOURNAL

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CONTENTS

1 Publisher, Editor in Chief, Managing Editor and Editorial Board

2 DECLINE OF REAL POWER LOSS BY UPGRADED ARTIFICIAL BEE COLONY ALGORITHM

MR.K.LENIN, B.RAVINDHRANATHREDDY, M.SURYAKALAVATHI

3 REDUCING THE DIMENSIONAL DEPENDENCE FOR RANK-BASED SIMILARITY SEARCH

JEEVAN ARJUN SHELKE, VIRESH SHIVSHANKAR HUMNABADKAR, TUSHAR TINAJIRAO KALE, GIRISH GUNDOPANT

KULKARNI, P. S. KULKARNI

4 IMPACT OF IRRIGATION PROJECT ON FADAMA COMMUNITY OF BAUCHI STATE NIGERIA

ABDULLAHI, A. S., B.G JAHUN, M. U. SABO

5 EXTENT AND CAUSES OF EUCALYPTUS TREE FARMING EEXPANSION IN EZA WEREDA,

ETHIOPIA

BELAY ZERGA

6 A STUDY ON APPLICATION OF NATURE INSPIRED ALGORITHMS FOR SOLVING REACTIVE

POWER PROBLEM

K. LENIN, B.RAVINDHRANATH REDDY, M.SURYA KALAVATHI


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Publisher: Elite Hall Publishing House

Editor in Chief:

Dr. Mohammad Mohsin (India)

E-mail: [email protected]

Editorial Board:

Mr. K. Lenin,

Assistant Professor, Jawaharlal Nehru

technological university Kukatpally, India


Dr. Jake M. Laguador

Professor, Engineering Department

Lyceum of the Philippines University, Batangas

City, Philippines


Dr. T. Subramanyam

FACULTY, MS Quantitative Finance, Department

of Statistics

Pondicherry Central University, India

Email: [email protected]

Dr. G. Rajarajan,

Professor in Physics, Centre for Research &

Development

Mahendra Engineering College, India


Miss Gayatri D. Naik.

Professor, Computer Engg Department, YTIET

College of Engg, Mumbai University, India


Mr. Rudrarup Gupta

Academic Researcher, Kolkata, India


Mr. Belay Zerga

MA in Land Resources Management, Addis

Ababa University, Ethiopia


Mrs.Sukanya Roy

Asst.Professor (BADM), Seth GDSB Patwari

College, Rajasthan,India


Mr. Nachimani Charde

Department of Mechanical, Material and

Manufacturing Engineering, The University of

Nottingham Malaysia Campus


Dr. Sudhansu Sekhar Panda

Assistant Professor, Department of Mechanical

Engineering

IIT Patna, India


Dr. G Dilli Babu

Assistant Professor, Department of Mechanical

Engineering,

V R Siddhartha Engineering College, Andhra

Pradesh, India


Mr. Jimit R Patel

Research Scholar, Department of Mathematics,

Sardar Patel University, India


Dr. Jumah E, Alalwani

Assistant Professor, Department of Industrial

Engineering,

College of Engineering at Yanbu, Yanbu, Saudi

Arabia


Web: http://ijaes.elitehall.com/

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DECLINE OF REAL POWER LOSS BY UPGRADED ARTIFICIAL

BEE COLONY ALGORITHM

Mr.K.Lenin1, Dr.B.RavindhranathReddy

2, Dr.M.Suryakalavathi

3

1Research Scholar,2Execuitive Engineer,3Professor ,

Department of Electrical and Electronics Engineering,

Jawaharlal Nehru Technological University,Kukatpally, Hyderabad 500 085, India

Corresponding author Email: [email protected].

Abstract

An artificial bee colony (ABC) algorithm is one of numerous swarm intelligence algorithms that employ the foraging behavior of honeybee

colonies. To improve the convergence performance and search speed of finding the best solution using this approach, we propose an

improved hybrid ABC algorithm (IABC) in this paper. Our main aspect is to minimize the real power loss and also to keep the variables

within the limits. Proposed Improved ABC (IABC) algorithm has been tested in standard IEEE 30 Bus test system and simulations results

reveal about the better performance of the proposed algorithm in reducing the real power loss and voltage profiles within the limits.

Keywords

artificial bee colony algorithm, swarm intelligence, optimal reactive power, Transmission loss.

Introduction

Optimal reactive power problem plays most important role in the stability of power system operation and control. In this

paper the main aspect is to diminish the real power loss and to keep the voltage variables within the limits. Previously many

mathematical techniques like gradient method, Newton method, linear programming [4-7] has been utilized to solve the optimal

reactive power dispatch problem and those methods have many difficulties in handling inequality constraints. Voltage stability

and voltage collapse play an imperative role in power system planning and operation [8]. Recently Evolutionary algorithms

like genetic algorithm have been already utilized to solve the reactive power flow problem [9,10].In [11-20] Genetic algorithm,

Hybrid differential evolution algorithm, Biogeography Based algorithm, fuzzy based methodology, improved evolutionary

programming has been used to solve optimal reactive power flow problem and all the algorithm successfully handled the

reactive power problem. The Artificial Bee Colony (ABC) algorithm was introduced by Karaboga [21] as a technical report,

then its performance was measured using benchmark optimization functions [22,23]. A recent study [24] showed that ABC

algorithm performs significantly better or at least comparable to other SI algorithms as genetic algorithm [25], DE, and PSO

algorithms. The ABC algorithm has been applied to several fields in various ways, for example, training neural networks [26];

solving sensor deployment problem[27]; applied for engineering design optimization [28].The ABC algorithm is superior to

other algorithms in terms of its simplicity, flexibility and robustness. In addition, the ABC algorithm requires fewer training


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parameters; so combining it with other algorithms is easier. The standard ABC algorithm was based on the results of some

standard benchmark problems, however, as an initial proposal; it still has a considerable performance gap with respect to

state-of the- art algorithms. In particular, it was found to have relatively poor performance on composite and non-separable

functions, and have a slow convergence rate toward high quality solutions. To improve the performance, the ABC algorithm

has been extended in a number of ways recently. For example, Alatas [29] proposed a chaotic ABC algorithm, in which many

chaotic maps for parameters adapted from the original ABC were introduced to improve its convergence performance; Zhu and

Kwong [30] proposed a global best (Gbest) guided ABC algorithm by incorporating the information of global best solution into

the solution search equation to improve the exploitation; Banharnsakun et al. [31] introduced best-so-far selection to standard

ABC algorithm;Karaboga and Gorkemli [32] introduced a combinatorial ABC for travelling salesman problems. In addition,

Gao and Liu [33] proposed a modified ABC algorithm (MABC) that used a modified solution search equation with chaotic

initialization, which excluded the probabilistic selection scheme and scout bees phases. Along with the advantages of the

improved versions of ABC, however, a few disadvantages still exist. For example, ABC algorithms have low convergence

speeds, low exploitation abilities, and are also easily trapped in local optima. To overcome these disadvantages, we focus on

the predominance of hybridizing other algorithms easily and propose an improved hybrid ABC algorithm, which inspired by

self-adaptive mechanism, incorporated DE (Differential evolution) and PSO (Particle swarm optimization) algorithms. The

proposed IABC algorithm has been evaluated in standard IEEE 30 bus test system. The simulation results show that our

proposed approach outperforms all the entitled reported algorithms in minimization of real power loss and also voltage profiles

are within the limits.

Objective Function

A. Active power lossActive power lossActive power lossActive power loss

The objective of the reactive power dispatch problem is to minimize the active power loss and can be defined in equations

as follows:

(1)

Where F- objective function, PL – power loss, gk - conductance of branch,Vi and Vj are voltages at buses i,j, Nbr- total

number of transmission lines in power systems.

B. Voltage profile improvementVoltage profile improvementVoltage profile improvementVoltage profile improvement

To minimize the voltage deviation in PQ buses, the objective function can be written as:

(2)


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Where VD - voltage deviation, - is a weighting factor of voltage deviation.

VD is the voltage deviation given by:

(3)

Equality Constraint

The equality constraint of the problem is indicated by the power balance equation as follows:

(4)

Where the total power generation PG has to cover the total power demand PD and the power losses PL.

Inequality Constraints

The inequality constraint implies the limits on components in the power system in addition to the limits created to make

sure system security. Upper and lower bounds on the active power of slack bus, and reactive power of generators are written as

follows:

(5)

(6)

Upper and lower bounds on the bus voltage magnitudes:

(7)

Upper and lower bounds on the transformers tap ratios:

(8)


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Upper and lower bounds on the compensators

(9)

Where N is the total number of buses, NT is the total number of Transformers; Nc is the total number of shunt reactive

compensators.

THE STANDARD ABC ALGORITHM

In the ABC algorithm, the artificial bee colony comprises three kinds of bees: employed bees, onlooker bees, and scout bees.

Employed bees search for food source sites by modifying the site in their memory, evaluating the nectar amount of each new

source, and memorizing the more productive site through a selection process. These bees share information related to the

quality of the food sources they exploit in the “dance area”. The number of employed bees is equal to the number of food

sources for the hive. Onlooker bees search for food sources based on the information coming from employed bees within the

hive. As such, more beneficial sources have higher probability to be selected by onlookers. Further, onlooker bees choose food

sources depending on the given information through probabilistic selection and modify these sources. When the food source is

abandoned, a new food source is randomly selected by a scout bee to replace the abandoned source. The number of food

sources in ABC algorithm is equivalent to the number of solutions in a population for an optimization problem. The number of

nectar sites of a food source represents the fitness cost of the associated solution.

The main steps of the standard ABC algorithm are given below:

1. Initialize the population of solutions xij with

xij = xmin, j + rand[0,1](xmax, j − xmin, j ) (10)

Where, i ∈1, 2, ..., SN and j ∈1, 2, ...,D are randomly selected indexes, SN is the number of food source, and D is the

dimension size.

2. Evaluate the population.

3. Initialize cycle to 1.

4. Produce new solutions vi for the employed bees by using (10), then evaluate them as follows

vij = xij + φij (xij − xkj ) (11)

where φij is a uniformly distributed random number in the range [-1,1]; i, k ∈1, 2, ..., SN are randomly selected indexes with k

different from i and j ∈1, 2, ...,D is a randomly selected index.

5. Apply the greedy selection process for the employed bees.

6. If the solution does not improve, add 1 to the trail, otherwise, set the trail to 0.

7. Calculate probability values Pi for the solutions using

(12) as

(12)


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where fiti is the fitness value of solution i.

8. Produce new solutions for the onlooker bees from solutions xi , which is selected depending on pi , then evaluate them.

9. Apply the greedy selection process for the onlooker bees.

10. If the solution does not improve, add 1 to the trail, otherwise, set the trail to 0.

11. Determine the abandoned solution for the scout, if it exists, and replace it with a new random solution using (10).

12. Memories the best solution achieved so far.

13. Add 1 to cycle.

14. Repeat until cycle reaches a predefined maximum cycle number (MCN).

Proposed IABC algorithm

There are two common aspects in population based heuristic algorithms, i.e., exploration and exploitation. Exploration is the

ability to expand the search space, and exploitation is the ability to find optima around a good solution. Exploration and

exploitation play key roles in SI algorithms. They coexist in the evolutionary process of algorithms such as PSO, DE, and ABC,

but they contradict each other. To achieve a good optimization performance with higher convergence speeds and not trapped in

local optima, a self-adaptive mechanism to change the search range related with a cycle number was introduced, and then

combined with DE to improve the performance of the employed bees. In the standard ABC algorithm, a random perturbation is

added to the current solution to produce a new solution. This random perturbation is weighted by φij selected from [-1,1] and is

an uniformly distributed real random number in the standard ABC. Too large or too small value of φij affects the convergence

speed. Therefore, a self-adaptive mechanism is used to balance the convergence speed and the exploration ability of the

algorithm for employed bees. The self-adaptive mechanism of ABC consists of very simple structure and is easy to implement.

The φij is changed with the cycle number according to a random value called rand in the range [0,1] for the food searching

process of an employed bee; φij is determined as (13).

(13)

The searching food source process in the standard ABC algorithm is similar to the mutation process of DE. Besides, in DE [34,

35], the best solution in the current population is very advantageous for higher convergence performance. As one scheme of the

mutations of DE, “DE/best/1” can effectively maintain population diversity. The “DE/best/1” mutation strategy was combined

with the food search process of the standard ABC algorithm to produce a new search equation (14) and improved the

convergence ability.

vij = xbest , j + φij (xij − xkj ) (14)

where i, k ∈1, 2, ..., SN are randomly selected indexes with k different from i ; j ∈1, 2, ...,D is a randomly selected index and

φij is the parameter given in (13).

It was determined that the search ability of the ABC algorithm is good at exploration, but poor in terms of exploitation.

Specifically, the relationship of employed bees and onlooker bees are focused on exploration and exploitation, respectively.


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Employed bees explore new food sources and send information to onlooker bees, and onlooker bees exploit the food sources

explored by employed bees. In the standard ABC algorithm, much time is required to find the food source due to poor

exploitation abilities and lower convergence speeds. To improve the exploitation ability and convergence performance of the

algorithm, we incorporated PSO [36] into the standard ABC algorithm. PSO is based on the simulation of simplified social

animal behaviors and it has the advantage of good convergence performance. We modified the onlooker bee search solution by

taking advantage of the search mechanism of PSO; our modified search equation for onlooker bees is shown as (15).

vij = xij + ϕij (xij − xkj ) +ψ ij (xbest , j − xij ) (15)

where i, k ∈1, 2, ..., SN are randomly selected indexes with k different from i ; j ∈1, 2, ..., SN is a randomly selected index;

xbest , j is the j-th element of the best dominant solution, and ϕij ∈[−1, 1] and ψ ij ∈[0, 1.2] are uniformly distributed random

numbers. The proposed IABC algorithm modified the standard ABC on step 4 and step 8. The modification (4) and (5) are

introduced to substitute (2) on step 4; the modification (6) is introduced to substitute (2) on step 8.

Simulation Results

Validity of the Improved hybrid ABC algorithm (IABC) algorithm has been verified by applying in IEEE 30-bus, 41 branch

system. And the system has 6 generator-bus voltage magnitudes, 4 transformer-tap settings, and 2 bus shunt reactive

compensators. Bus 1 is taken as slack bus and 2, 5, 8, 11 and 13 are taken as PV generator buses and the rest are taken as PQ

load buses. Control variables limits are given in Table I.

TABLE I. VARIABLE LIMITS (PU)

List of Variables Min. Max. Type

Generator Bus 0.91 1.11 Continuous

Load Bus 0.94 1.03 Continuous

Transformer-Tap 0.94 1.03 Discrete

Shunt Reactive

Compensator -0.10 0.30 Discrete

In Table II the limits of generators has been given as follows,

TABLE II. GENERATORS POWER LIMITS

Bus Pg Pgmin Pgmax Qgmin

1 98.00 50 201 -20

2 81.00 21 80 -20

5 53.00 15 52 -15


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8 21.00 10 33 -15

11 21.00 10 28 -10

13 21.00 12 40 -15

TABLE III. VALUES OF CONTROL VARIABLES AFTER OPTIMIZATION

List of Control Variables IABC

V1 1.0610

V2 1.0522

V5 1.0308

V8 1.0409

V11 1.0812

V13 1.0616

T4,12 0.00

T6,9 0.01

T6,10 0.90

T28,27 0.90

Q10 0.12

Q24 0.12

Real power loss 4.2891

Voltage deviation 0.9090

Table III shows the control variables are within limits.

And Table IV summarizes the comparison results of the optimal solution obtained by various methods.

TABLE IV. COMPARISON RESULTS

Techniques Real power loss (MW)

SGA (37) 4.98

PSO (38) 4.9262

LP (39) 5.988

EP (39) 4.963

CGA (39) 4.980

AGA (39) 4.926

CLPSO (39) 4.7208

HSA

(40) 4.7624

BB-BC (41) 4.690

IABC 4.2891


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Conclusion

In this paper, improved hybrid ABC algorithm (IABC) has been productively implemented to solve reactive power

problem. Proposed improved hybrid ABC algorithm (IABC) successfully handles the equality and inequality constraints. The

validity of the improved hybrid ABC algorithm (IABC) has been proved by testing it in standard IEEE30bus system. The

results are compared with the other heuristic methods and the improved hybrid ABC algorithm (IABC) established its

efficiency and strength in minimization of real power loss. And control variables are well within specified limits.

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[29] B. Alatas, “Chaotic bee colony algorithm for global numericaloptimization,” Expert Systems with Applications, Vol. 37, pp. 5682-5687, 2010.

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[41] S. Sakthivel, M. Gayathri, V. Manimozhi, “A Nature Inspired Optimization Algorithm for Reactive Power Control in a Power System”, International Journal of Recent Technology and Engineering (IJRTE) ,pp29-33 Volume-2, Issue-1, March 2013.


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REDUCING THE DIMENSIONAL DEPENDENCE FOR RANK-BASED

SIMILARITY SEARCH

Jeevan Arjun Shelke

NBN sinhgad School Of Engineering Vadgoan, Pune

[email protected]

Viresh Shivshankar Humnabadkar


[email protected]

Tushar Tinajirao Kale

NBN sinhgad School Of Engineering Vadgoan, [email protected]

Girish Gundopant Kulkarni


[email protected]

Prof. P. S. Kulkarni

Asst. Prof.


[email protected]

Abstract: In this paper a data structure for k-NN search, the Rank Cover Tree (RCT) is implemented. The pruning tests for

RCT rely on the comparison of similarity values not on the other properties of the underlying space, such as the triangle

inequality. Objects are selected according to their ranks with respect to the query object, allowing much tighter control on the

overall execution costs. Theoretical analysis shows that with very high probability, the RCT returns a correct query result in

time that depends very competitively on a measure of the intrinsic dimensionality of the data set. The experimental results for

the RCT show that non-metric pruning strategies for similarity search can be practical even when the representational

dimension of the data is extremely high. They also show that the RCT is capable of meeting or exceeding the level of

performance of state-of-the-art methods that make use of metric pruning or other selection tests involving numerical

constraints on distance values.

Keywords: Nearest neighbor search, intrinsic dimensionality, rank-based search.

1. Introduction

The fundamental operations in data mining are classification, cluster analysis, and outlier detection, and this might be most

widely-encountered is that of similarity search. Similarity search is that the foundation of k-nearest-neighbor (k-NN)


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classification, which frequently produces competitively low error rates in practice, significantly once the quantity of

categories is massive [26]. The error rate of nearest-neighbor classification has been shown to be ‘asymptotically

optimal’ because the training set size will increase [14]. For clustering, several of the foremost effective and

commonwaysneed the determination of neighbor sets based mostlyat a considerable proportion of the data set objects [26]:

examples include hierarchical (agglomerative) strategies like ROCK [22] and CURE [23]; density-based

strategieslikeDBSCAN [17], OPTICS [3], and SNN [16]; and non-agglomerative shared-neighbor clustering [27]. A

content-based filtering strategy for recommender systems and anomaly detection strategies [11] ordinarily build use of k-NN

techniques, either through the direct use of k-NN search, or by means that of k-NN cluster analysis. a

very common density-based live, the local Outlier factor (LOF), depends heavily on k-NN set computation to

see the denseness of the data within the section of the test point [8].

For data mining applications based on similarity search, data objects are usually modeled as feature vectors of

attributes that some measure of similarity is defined. Often, the data can be modeled as a subset belonging to a metric

space over some domain , with distance measure satisfying the metric postulates. Given a query

point , similarity queries over are of two general types:

• K-nearest neighbor queries report a set of size k elements satisfying for all

and .

• Given a real value , range queries report the set .

While a k-NN query result is not necessarily unique, the range query result clearly is.

Motivated a minimum of in part by the impact of similarity search on issues in data mining, machine learning, pattern

recognition, and statistics, the planning and analysis of scalable and effective similarity search structures has been the

subject of intensive research for several decades. Till comparatively in recent years, most data structures for similarity search

targeted low-dimensional real vector spacer presentations and therefore the Euclidean or alternative L-P distance metrics.

However, several public and commercial data sets available these days are additional naturally depicted as vectors

spanning several hundreds or thousands of feature attributes, which might be real or integer-valued, ordinal or categorical, or

perhaps a mix of those types. This has spurred the development of search structures for additional general metric areas, like the

Multi-Vantage-Point Tree [7], the Geometric Near-neighbor Access Tree (GNAT) [9], spatial Approximation Tree (SAT), the

M-tree [13], and (more recently) the cover Tree (CT) [6].

Despite their various advantages, spatial and metric search structures are both limited by an effect often referred to as

the curse of dimensionality. One way in which the curse may manifest itself is in a tendency of distances to concentrate


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strongly around their mean values as the dimension increases. Consequently, most pairwise distances become difficult to

distinguish, and the triangle inequality can no longer be effectively used to eliminate candidates from consideration along

search paths. Evidence suggests that when the representational dimension of feature vectors is high (roughly 20 or more [5]),

traditional similarity search accesses an unacceptably-high proportion of the data elements, unless the underlying data

distribution has special properties [6], [12]. Even though the local neighborhood information employed by data mining

applications is useful and meaningful, high data dimensionality tends to make this local information very expensive to obtain.

The performance of similarity search indices depends crucially on the way in which they use similarity information

for the identification and selection of objects relevant to the query. Virtually all existing indices make use of numerical

constraints for pruning and selection. Such constraints include the triangle inequality (a linear constraint on three distance

values), other bounding surfaces defined in terms of distance (such as hyper cubes or hyperspheres) [25], [32], range queries

involving approximation factors as in Locality-Sensitive Hashing (LSH) [19], [30], or absolute quantities as additive distance

terms [6]. One serious drawback of such operations based on numerical constraints such as the triangle inequality or distance

ranges is that the number of objects actually examined can be highly variable, so much so that the overall execution time

cannot be easily predicted.

In an attempt to improve the scalability of applications that depend upon similarity search, researchers and

practitioners have investigated practical methods for speeding up the computation of neighborhood information at the expense

of accuracy. For data mining applications, the approaches considered have included feature sampling for local outlier detection

[15], data sampling for clustering and approximate similarity search for k-NN classification (as well as in its own right).

Examples of fast approximate similarity search indices include the BD-Tree, a widely-recognized benchmark for approximate

k-NN search; it makes use of splitting rules and early termination to improve upon the performance of the basic KD-Tree. One

of the most popular methods for indexing, Locality-Sensitive Hashing [19], [30], can also achieve good practical search

performance for range queries by managing parameters that influence a tradeoff between accuracy and time. The spatial

approximation sample hierarchy (SASH) similarity search index [29] has had practical success in accelerating the performance

of a shared-neighbor clustering algorithm [27], for a variety of data types.

In this paper, we propose a new similarity search structure, the Rank Cover Tree (RCT), whose internal operations

completely avoid the use of numerical constraints involving similarity values, such as distance bounds and the triangle

inequality. Instead, all internal selection operations of the RCT can be regarded as ordinal or rank-based, in that objects are

selected or pruned solely according to their rank with respect to the sorted order of distance to the query object. Rank

thresholds precisely determine the number of objects to be selected, thereby avoiding a major source of variation in the overall

query execution time. This precision makes ordinal pruning particularly well-suited to those data mining applications, such as

k-NN classification and LOF outlier detection, in which the desired size of the neighborhood sets is limited. As ordinal pruning


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involves only direct pairwise comparisons between similarity values, the RCT is also an example of a combinatorial similarity

search algorithm [21].

The main contributions of this paper are as follows:

• A similarity search index within which only ordinal pruning is employed for node selection—no use is formed of metric

pruning or of different constraints involving distance values.

• Experimental proof indicating that for practical k-NN search applications, our rank-based technique is

extremely competitive with approaches that build specific use of similarity constraints. Specially, it comprehensively

outperforms progressive implementations of each LSH and therefore the BD-Tree, and is capable of

achieving practical speedups even for data sets of extraordinarily high representational dimensionality.

• A formal theoretical analysis of performance showing that RCT k-NN queries efficiently manufacture correct results

with very high chance. The performance bounds are} expressed in terms of a measure of

intrinsic spatiality (the expansion rate [31]), independently of the complete objective dimension of the information set.

The analysis shows that by accepted polynomial sublinear dependence of question value in terms of the quantity of

data objects n, the dependence on the intrinsic dimensionality is less than the other known search index achieving

sublinear performance in n, whereas still achieving terribly high accuracy.

To the best of our knowledge, the RCT is the first practical similarity search index that both depends solely on ordinal

pruning, and admits a formal theoretical analysis of correctness and performance. A preliminary version of this work has

appeared in [28].

The remainder of this paper is organized as follows. Section 2 briefly introduces two search structures whose designs

are most-closely related to that of the RCT: the rank-based SASH approximate similarity search structure [29], and the

distance-based Cover Tree for exact similarity search [6]. Section 3 introduces basic concepts and tools needed to describe the

RCT. Section 4 presents the algorithmic details of the RCT index.

2. LITERATURE SURVEY

1. Michael E. Houle And Michael Nett,” Rank-Based Similarity Search: Reducing The Dimensional Dependence”,

IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 37, No. 1, January 2015.


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In this paper new structure for similarity search, the Rank Cover Tree, whose ordinal pruning strategy makes use only of

direct comparisons between distance values. The RCT construction and query execution costs do not explicitly depend

on the representational dimension of the data, but can be analyzed probabilistically in terms of a measure of intrinsic

dimensionality, the expansion rate. Investigation and compression of a performance of different approaches to exact

and approximate k-nearest neighbor search in general metric spaces. The experimental evaluation assessed the query

performance of the various methods in terms of the tradeoff between accuracy and execution time is given.

2. A. Beygelzimer, S. Kakade, and J. Langford, “Cover trees for nearest neighbor,” in Proc. 23rd Int. Conf. Mach.

Learn., 2006, pp. 97– 104.

A Cover Tree is a data structure helpful in calculating the nearest neighbor of points given only a metric. A cover tree is

particularly motivating for a confluence of reasons:

1. The running time of a nearest neighbor query is only O(log(n)) given a fixed intrinsic dimensionality. (like KR2002

and KL04)

2. The space usage and query time are O(n) under no assumptions. (like the naive approach, sb(s), and ball trees)

3. It's remarkably fast in practice.

3. RELATED WORK

This paper are going to be involved with two recently-proposed approaches that on the surface appear quite dissimilar: the

SASH heuristic for approximate similarity search [29], and the cover Tree for exact similarity search [6]. Of the two, the

SASH is often considered combinatorial, whereas the cover Tree makes use of numerical constraints. Before formally stating

the new results, we have a tendency to first provide an outline of each the SASH and also the cover Tree.

1. SASH

For large data sets, we should use data structures that permit far better performance on the amount N of items within

the database. This will be illustrated by the role that R-Trees play in the efficiency DBSCAN. To

manage very massive data sets, we've SASH. The SASH makes minimal assumptions concerning the nature of the metric for

associative queries. It additionally doesn't enforce a partition of the search space, as for instance R-Trees do. For approximate

k-NN (k-ANN) queries on the large sets, the SASH systematically returns a high proportion of truth k-NNs at speeds of

roughly two orders of magnitude quicker than sequential search. The SASH has already been successfully applied to

clustering and navigation of very large, very high dimensional text data sets. The SASH internally uses a

k-NN query on small sets. A (SASH) may be a multi-level structure recursively constructed by building a SASH on a

half-sized random sample S'⊂S of the object set S, so connecting every object remaining outside S' to many of its approximate


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nearest neighbors from at intervals S'. Queries are processed by initial locating approximate neighbors at intervals sample

S', so exploitation the pre-established connections to find neighbors at intervals the rest of the information set. The SASH

index depends on a pairwise distance measure, however otherwise makes no assumptions relating to the illustration of the

information, and doesn't use constellation difference for pruning of search ways.

SASH construction is in batch fashion, with points inserted in level order. Every node seems at one level of the

structure: if the leaf level is level 1, the probability of being allotted to level is . Every node υ is connected to at the

most parent nodes, for a few constant , chosen as approximate nearest neighbors from among the nodes at one

level more than . The SASH guarantees a continuing degree for every node by guaranteeing that every will function the

parent of at the most children; any decide to attach more than children to an individual parent is resolved by

accepting solely the nearest children to , and reassigning rejected kids to close surrogate oldsters whenever necessary.

Similarity queries are performed by establishing an upper limit on the number of neighbor candidates to be retained

from level of the SASH, dependent on both and the number of desired neighbors’ . The search starts from the root and

progresses by successively visiting all children of the retained set for the current level, and then reducing the set of children to

meet the quota for the new level, by selecting the elements closest to the query point.

2. Cover Trees and the Expansion Rate

In [31], Karger and Ruhl introduced a measure of intrinsic dimensionality as a means of analyzing the performance of a local

search strategy for handling nearest neighbor queries. In their method, a randomized structure resembling a skip list is used to

retrieve pre-computed samples of elements in the vicinity of points of interest. Eventual navigation to the query is then

possible by repeatedly shifting the focus to those sample elements closest to the query, and retrieving new samples in the

vicinity of the new points of interest.

The expansion rate of S is the minimum value of such that the above condition holds, subject to the choice of

minimum ball set size b.

The Cover Tree can also be used to answer approximate similarity queries using an early termination strategy.

However, the approximation guarantees only that the resulting neighbors are within a factor of of the optimal distances,

for some error value > 0.

4. RANK COVER TREE


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Some of the design features of the SASH similarity search structure and the Cover Tree are used in proposed Rank Cover Tree.

Like the SASH (and unlike the Cover Tree) we shall see that its use of ordinal pruning allows for tight control on the execution

costs associated with approximate search queries. By restricting the number of neighboring nodes to be visited at each level of

the structure, the user can reduce the average execution time at the expense of query accuracy.

In the RCT, a tree T imposed on a random leveling of the data set S. Given any , the subtree

spanning only the level sets is also a Rank Cover Tree for the set ; will be referred to as

the partial Rank Cover Tree of T for level l. Now, for any and any choice of l < j < h, we define to be the

unique ancestor of u in at level j.

RCT search proceeds from the root of the tree, by identifying at each level j a set of nodes (the cover set) whose

subtrees will be explored at the next iteration. For an item u to appear in the query result, its ancestor at level j must appear in

the cover set associated with level j. is chosen so that, with high probability, each true k-nearest neighboru satisfies the

following conditions: the ancestor of u is contained in , and for any query point q, the rank of

with respect to Lj is at most a level-dependent coverage quota .

The real-valued parameter is the coverage parameter. It influences the extent to which the number of requested

neighbors k impacts upon the accuracy and execution performance of RCT construction and search, while also establishing a

minimum amount of coverage independent of k.

Offline construction of the RCT is performed by level ordered insertion of the items of the random leveling, with the

insertion of node performed by first searching for its nearest neighbor using the partial Rank Cover

Tree , and then linking v to w.

A Rank Cover Tree T will be said to be well-formed if for all nodes with parent , the parent v is the

nearest neighbor of u from among the nodes at that level—that is, if . In the analysis to follow, we determine

conditions upon the choice of the coverage parameter for which the construction algorithm produces a well-formed RCT

with high probability. We also derive bounds on the error probability for k-NN queries on a well-formed RCT.

5. EXPERIMENTAL SETUP

The system is built using Java framework (version jdk 8) on Windows platform. The Netbeans (version 8.1) is used as a

development tool. The system doesnt require any specific hardware to run any standard machine is capable of running the


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application.

6. CONCLUSION

We implemented data structure which is replacement data structure for K-NN, the Rank cover Tree, that uses direct

comparisons between distance values. The RCT construction andqueryexecutioncosts is freelanceon

therepresentationaldimension of the data, however are oftenanalyzedprobabilistically in terms of a measure of

intrinsicdimensionality.The theoretical analysis, shows that the RCT outperforms its twonearest relatives—the cover Tree and

SASH structures -in several cases, and consistentlyoutperforms the E2LSH implementation of LSH, classical indices such

as the KD-Tree and BD-Tree, and—for data sets of high (but sparse) dimensionality— the KD-Tree

ensemble technique FLANN.

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[29] M. E. Houle and M. Nett, “Rank cover trees for nearest neighbor search,” in Proc. Int. Conf. Similarity Search

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IMPACT OF IRRIGATION PROJECT ON FADAMA COMMUNITY

OF BAUCHI STATE NIGERIA

Abdullahi, A. S.1; B.G Jahun

1 and M. U. Sabo

2

1Agricultural and Bioresource Engineering Department, Abubakar Tafawa Balewa University,

Bauchi State, Nigeria

2Crop Production Department, Abubakar Tafawa Balewa University, Bauchi State, Nigeria

ABSTRACT

A Study was carried out to assess the impact of irrigation project on Fadama Community in Western zone of Bauchi State,

Nigeria. The total Fadama land in the zone is 5,178ha. The Fadama is found within the strips of Gongola and Jama’are river

systems. A total of 90 detailed structured questionnaire and random sampling techniques were used in 30 locations. Farmers’

annual income, age, status, problems faced and farm size were considered. The data were analyzed using descriptive statistics.

The result indicates good use of facilities like wash bores, pumps and fertilizers. Major constrains faced by the farmers

includes pests, storage/processing facilities and cost of fuel. The expansion of the project by the World Bank is aimed to

address these impediments.

Keywords: Fadama, Irrigation facilities, Annual income, pests and Social Factors.

Email address of the Corresponding Author: [email protected]

INTRODUCTION

The overall objectives of agricultural development in Nigeria like any other developing nation are to

ensure adequate food supplies; increases export of crop production, produce raw materials for domestic

industries and create rural employment opportunities. For the rapidly increasing rural and urban

population therefore, food must be provided in sufficient and wholesome forms to meets their ever

increasing demands (Ogazi, 1996; Tansey and Worsley, 2014). Efforts to promote agricultural

development have been complemented by various government or programme. Some of these include

National Accelerated Food Production Programme (NAFPP) in 1972, Operation Feed the Nation (OFN)

in 1976. River Basin Development Authorities (RBDA) in 1976, Green Revolution in 1980, Go Back to

Land Programme in 1984, Directorate of Food Roads and Rural Infrastructure (DFRRI) in 1986, People’s

Bank of Nigeria (PBN) in 1990 (Ani, 1999).

In an attempt to reduce the poverty level among rural Nigerians and also to increase the incomes and

productivity of the rural dwellers as a strategy of meeting up with millennium development goals of food


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sufficiency and poverty eradication, the Nigerian Government in collaboration with the World Bank came

up with Fadama irrigation project and Bauchi State is one of the beneficiaries States (Simonyan and

Omolehin, 2012).

“Fadama” as adopted by the World Bank, is a local „‟Hausa language’’ word referring to low-lying

moist areas consisting of alluvial deposits and containing extensive exploitable aquifers (Adesoji,

Farinde, and Ajayi, 2006; Ahmed, 2006; Girei and Dire, 2013; Qureshi, 1989) defined Fadama as alluvial

lowlands formed by erosional and depositional actions of rivers and

streams which possess fine textured and less acidic soils that are rich in organic matter. (Anaso, 1994)

viewed Fadama as having a broad embracing seasonally flooded or flooded lying land which can be

cultivated under residual moisture condition or under irrigation due to availa ble ground water during the

dry season. Flood plains or Fadama lands are usually more fertile and have higher moisture retention than

the surrounding uplands (Singh & Babaji, 1990). Fadama lands in Bauchi State have great potentials for

irrigation. They are easily exploitable through the use of shallow tube wells, wash bores, and streams.

Water is lifted with the help of low cost pumps, which are easily affordable by most farmers, (Graham,

Alabi , and Pishiria, 2003).

The National Fadama Development Programme (NDP) established in 1992 is one of the numerous

agricultural development programme embarked upon by government to ensure food security and poverty

alleviation. Fadama are the most productive areas in the northern states of Nigeria because of their

ecological peculiarities (Ani, 1999). Before the introduction of modern irrigation systems, some lands

were used to produce arable crops like rice, maize and vegetables. Most of these, with the exception of

rice, are grown entirely on residual moisture. Irrigation was also achieved using water raised from river,

streams or shallow wells by means of Shadoof or Jigo. Lifting water by this method is laborious and

limits the irrigable area to about 0.1 ha per Shadoof (Umara) 2016. The introduction of pumps for

irrigation dramatically changes the cropping patterns on Fadama lands. The NFDP were mandated to

accelerate the pace of small-scale irrigation development in Nigeria through intensive cultivation of

low-lying flood plains (Uche, 2011). Bauchi State is actively participating in the programme since 1993.

The World Bank, Federal and State governments co-jointly fund the NFDP. The aim of the study is to

determine the impact of irrigation project on Fadama irrigation Community with specific objectives as:

a) To determine farmers annual income as a result of the project intervention

b) To determine the farmers’ access to facilities such as water pumps, wash bores, seed,

pesticides and fertilizer

c) To identify some of the problems faced by farmers.

MATERIAL AND METHODS


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Location and Climate: Bauchi state is located at latitude 10017’ North and longitude 9

049’ East with

altitude 690.2m above sea level (Kowal, Knabe, and Committee, 1972; Ross, 1998). The vegetation for

the state consists of open savannah wood land, with trees of about 6m or higher. The trees occur in

clusters or single, the spaces between the trees are occupied by non-woody herb species with height up to

3m (Garba and Renard, 1991). The study was conducted in the western zone of Bauchi State, Nigeria and

the zone consists of seven Local Government Areas. The state is politically divided into three zones

namely: Northern, Western and the Central zones. The Fadama lands of Bauchi state are found within the

strips of land adjoining the banks of the river systems (5,178 ha). These include the Dilime/Bungtal,

Jama’are and Kari/Dingaiya system drain. Others are Komadugu and old Gongola/Dajin river systems.

The Fadama

locations in the southern Bauchi falls under two river systems (Gongola and Jama’are) with many lakes

that make Fadama lands most profitable for dry season farming. The soils are alluvial in nature,

consisting of clay’s silts sands, sandy loam and mineral particles of various combinations. The top soil

has moderate to high fertility and the alluvium deposit is up to 10m thick (Bouwman, 1990). Table 1

shows location where Fadama Users Association (FUA) exists in the zone as shown in Appendix I. FUA

members selected for the study where those who benefited from the NFDP loan package in 1997.

The data for the study were obtained from farmers through detailed structured questionnaire.

Random sampling techniques were used to select 86 respondents from 30 villages/towns. A total of 90

questionnaires were distributed and 86 were returned and used for the study. The data were collected in

form of interview schedules with farmers for each location visited. Descriptive statistics were used in this

study. The descriptive statistics involved the use of frequency distribution and percentages as reported by

(Muhammad, Umar, Abubakar, and Abdullahi, 2011). Primary data was used for the study and included

respondents personal background, production inputs, and cost of production, income and expenditure,

accessibility to basic amenities among others. Data collection was facilitated with the aid of trained staff

selected from the planning, monitoring and evaluation department of Bauchi State Agricultural

Development Programme.

Theoretical and Methodical Framework Net farm income method was used to evaluate and compared the income of irrigation project on

beneficiary farmers in the study area. The model specifications for the net farm income as reported by

(Simonyan and Omolehin, 2012) are as follows:

NFI = GFI −TVC −TFC 1)

Where;

NFI = Net Farm Income

GFI = Gross Farm Income

TVC = Total Variable Cost


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TFC = Total Fixed Cost

%change in income =

Income after - Income Before

2)

Income Before

The cross-sectional comparisons of farmers’ household income in the project cannot completely

attribute difference in income to programme intervention as such the study also employed

quasi-experiment using difference in difference estimator (Double difference) method to assess the impact

of irrigation project on income of beneficiary farmers.

The quasi-experiment is one of the impact assessment methods which involved selection of

respondents that participated in a program (beneficiary) from the same location who have similar

observable characteristics (Baker, 2000; Chen, Mu, and Ravallion, 2006; Renkow, 2011).

The double-difference analytical tool is a quantitative method often used to estimate and compare

change in outcome pre and post program for participant and non-participant (Chen et al., 2006). In order

to use the estimator in question, there must be information on both participant all individuals must be

observed both before and after the program (Smith, Smith, andVerner, 2006).

RESULTS AND DISCUSSION

Farmers’ Annual Income from the Fadama Project

The average output in monetary value obtained by the Fadama irrigation beneficiaries before and after the

project as well as percentage change in income due to project intervention shows the distribution of

farmers according to their annual income by participating in the Fadama irrigation activities. From the

results as presented in the Figure 1, 11.6% respondents were getting N5, 000.00 per annum, 25.6% above

N30, 000.00 for accepting the innovation of the projects. Similarly, 30.2 and 32.6% were between N15,

000.00 – N30, 000.00 respectively per annum. The respondents indicated that there is difference from

their income when compared with rain fed farmers for same kind of farm produce. This is not

unconnected with the high demand of fresh Fadama crops during dry season. Danjuma et al., (2016) in

their study on the Socio-Economic Impact of Fadama III Project in Taraba State also reported similar

findings among the farmers. The results of the study on the analysis of impact of Fadama irrigation

Project on beneficiary farmers income in Kaduna State indicates an increase in the net farm income of

both groups after Fadama II project, but the net farm income of the beneficiaries was higher (Simonyan

and Omolehin, 2012).


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Fig 1: Annual income from Fadama irrigation activities of farmers

Social factors of Fadama Community

The study indicated that factors like age, farmer’s status, house hold size and farm size have influence on

Fadama irrigation activities. Figure 2, shows the various factors which contribute to an increased

production on Fadama irrigation activities. Only 4.7% of the farmers fall between 18-25 years while 29

and 38.4% were 26 – 45 years respectively. Generally, the results show that most of the farmers have

dependents like wives, children and other relatives as 97.7% of the respondents were married for good

yield (harvest) additional labor is required to cultivate large area. The results inferred that labor have to be

hired for number of operations like planting, spraying chemicals etc. where the size of the family is small.

However, it could be deduce from the result that a farmer with larger family has little dependent on hired

labor and increased farm size (Adedayo, 2009).


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Fig 2: Social factors influencing Fadama irrigation activities

Farmers’ access and use of Fadama irrigation facilities in the Community

Several innovations and facilities were provided for use by the farmers under the Fadama irrigation

project. This study determine whether the farmers in the study were making use of the facilities which

includes: water pump, wash bore, and tube well, streams, fertilizers, and extension services. Figure 3

shows that 90.7% and 81.4% were using water pumps and fertilizer. Similarly, 45.4% and 50% uses

streams and wash bore for irrigating their crops respectively. Use of improved seeds, chemicals

(pesticides and herbicides) and extension services records 81.4%, 58% accordingly. The result indicates a

good response in terms of use of such facilities. It could be deduced that only few farmers 3% uses

Shadoof to lift water for irrigating their crops. This may be due to shallow water table in their areas.

According to Okojie (2009) both petrol and diesel pumps are used for Fadama irrigation in Bauchi,

Borno, Kwara, Plateau and Adamawa States.

Fig 3: Access to Fadama irrigation facilities by the Farmers


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Major Problems faced by the Farmers in the study area

Many farmers own water pumps, and farmers tend to hire if they don’t have. The distribution as shown in

Fig 4 reveals that, operating and maintenance of water pump was not a severe problem as reported by

about 7 and 0.7 percent of the respondents. Only 26.5 percent of the respondents indicated the problem

for the costs of spare parts for water pumps, while 87 percent expressed problems of costs of fuel which is

a scarce commodity in the rural set up. Pests and diseases affected the crops in the irrigation schemes with

91.9 percent as a very severe problem. The findings indicate that there is gap in making the farmers

embrace organic and biological control methods. This is in view of realization that chemical residue may

be harmful not only to the environment but the growers and consumers alike (Balogun, Aliyu, and Musa,

2013). The study further revealed that, about 76.7 percent of the respondents reported that lack of storage

facilities was also a severe problem, while 74 percent were processing facilities faced by the farmers. The

availability and accessibility of inputs for production at affordable cost at the right time by the

government improves profitability and reduces risk associated with agricultural production thereby

ensuring higher participation in the irrigation crop production activities (Dorward, 2009).

Fig 4: Distribution of major problems faced by farmers in the Fadama irrigation Community

Conclusions

The institutional approach adopted by the World Bank to assist Agricultural Development Project in

Bauchi State through the NFDP has transformed not only the cultural practice of a rural farmer but also

raised living standard. Farmers have now realized the importance of farming organization/Association to

derive benefit from governments or donors. They were enlightened on use of pumps, wash bore,

improved seeds and use of chemicals pesticides and fertilizer to boost their production. The output levels

of crops grown by farmers in the study area have increased over years, which results in significant

reduction in poverty. Despite some problems, Fadama Irrigation project has recorded success in the state.

The success has attracted its expansion by the World Bank. Based on this study, the following were


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suggested towards improved Fadama activities:

i. To develop a market, storage and processing outlet for Fadama crops, so that farmers can disburse their produce easily.

ii. The state ADP should establish stores/shops in major towns with Fadama irrigation activities.

Such stores should be stored with inputs like fertilizer, seeds, pesticides, sprayers, pump and

spare parts for easily access by farmers during peak demand period. (September to November

each year).

iii. Youth should be encouraged further to participate in Fadama irrigation activities. From the

study majority of the farmers 38.4% are between 45 – 46 years old. Such farming skill will

provide them self-employment and reduce poverty.

iv. With the increase in level of Fadama irrigation activities in the western zone, BSADP should

explore market potentials where demands for such crops are relatively high.

v. Associated problems such as pollution from rivers and dams from runoff and diseases reduce

the productivity and welfare of the people engaged in irrigation as observed by Igwe and

Onyenweaku (2013) and Adebayo and Tukur (2003). These problems can be addressed

through community participation and health education.

REFERENCES

Adebayo, A., and Tukur, A. (2003). Farmers’ Perception of Environmental Problems in Adamawa State,

Nigeria. African Journal of Environmental Management, 1.

Adedayo, A. (2009). Irrigation and Rural Welfare: Implications of Schistosomiasis among Farmers in

Kazaure LGA, Jigawa State, Nigeria. Journal of Agricultural Research and Development, 2(1), 52-59.

Adesoji, S., Farinde, A., and Ajayi, O. (2006). Extension Work Development in Osun State, Nigeria.

Journal of Applied Sciences, 6(15), 3089-3095.

Ahmed, G. (2006). An Overview of Fadama II Project. Proceeding of Adamawa State Fadama

Development Sensitization Workshop, May 9th 2006.

Anaso, A. B. (1994). “Crop Production in fadama fields of northern Nigeria”, Kolawole, A.,

Scoones.,Awogbade,

M.O. and Voh, J.P. (eds.). Strategies for Sustainable Use of Fadama Land in Northern Nigeria. ITED

Publishers, ABU Zaria.


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Ani, A. (1999). Analysis of the Performance of Rural Farmers in the Fadama Users Association (FUA)

Programme in the Northern Zone of Bauchi State. Nig. J. Trop. Agric, 1, 36-40.

Baker, J. L. (2000). Evaluating the impact of development projects on poverty: A handbook for

practitioners: World Bank Publications.

Balogun, O., Aliyu, T., and Musa, A. (2013). Perception of “Fadama” III Participating Farmers on Pests

and Diseases and the use of Integrated Pest Management Control Strategy in Kwara State, Nigeria.

Ethiopian Journal of Environmental Studies and Management, 6(6), 601-610.

Bouwman, A. (1990). Global distribution of the major soils and land cover types. Soils and the

Greenhouse Effect, 33-59.

Chen, S., Mu, R., and Ravallion, M. (2006). Are There Lasting Impacts of Aid to Poor Areas?: Evidence

from Rural China (Vol. 4084): World Bank, Development Research Group, Poverty Team.

Danjuma, I. A. O., Oruonye, E.D and Ahmed, Y.M. (2016). The Socio-Economic Impact of Fadama III

Project in Taraba State: A Case Study of Jalingo Local Government Area. International Journal of

Environmental & Agriculture Research (IJOEAR), 2(2), 35-41.

Dorward, A. (2009). Rethinking Agricultural Input Subsidy Programmes in a Changing World [Prepared

for FAO]. Garba, M., and Renard, C. (1991). Biomass production, yields and water use efficiency in some

pearl millet/legume cropping systems at Sadore, Niger. Int Assoc of Hydrological Sciences,

Wallingford,(Engl). 1991.

Girei, A., and Dire, B. (2013). Profitability and technical efficiency among the beneficiary crop farmers of

National Fadama II Project in Adamawa State, Nigeria. Net J. Agric. Sci, 1(3), 87-92.

Graham, W. B. R., Alabi , J. B., and Pishiria, I. W. (2003). Water and Agriculture in Sokoto Rima, Basin 3.

An appraisal of small scale Proceedings of the fourth International Conference and 25th Annual General

meeting of the Nigerian Institution of Agricultural Engineers, 25 128.

Igwe, K., and Onyenweaku, C. Optimum Combination of Farm Enterprises among Smallholder Farmers

in Umuahia Agricultural Zone, Abia State, Nigeria.

Kowal, J. M., Knabe, D. T., and Committee, H. T. (1972). An agroclimatological atlas of the northern

states of Nigeria, with explanatory notes.

Muhammad, H., Umar, B., Abubakar, B., and Abdullahi, A. (2011). Assessment of Factors Influencing


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Beneficiary Participation in Fadama II Project in Niger State, Nigeria. Nigerian Journal of Basic and

Applied Sciences, 19(2).

Ogazi, P. O. (1996). Plantain: production, processing, utilisation: Paman and Associates.

Okojie, C. (2009). Decentralization and public service delivery in Nigeria: International food policy

research institute (IFPRI).

Qureshi, A. A. (1989). National Water Management in Fadama Areas. Paper presented at the National

Workshop on fadama and irrigation Development in Nigeria, Bauchi, 23rd – 26th October, 1989.

Renkow, M. (2011). Impacts of IFPRI s Priorities for Pro-poor Public Investment Global Research

Program (Vol. 31): Intl Food Policy Res Inst.

Ross, R. (1998). Water treeing theories-current status, views and aims. Paper presented at the Electrical

Insulating Materials, 1998. Proceedings of 1998 International Symposium on.

Simonyan, J., and Omolehin, R. (2012). Analysis of Impact of Fadama II Project on Beneficiary Farmers

Income in Kaduna State: A double difference method approach. International Journal of Economics and

Management Sciences, 1(11), 1-8.

Singh, B., and Babaji, G. (1990). Characteristics of the soil in Dundaye District. 2. The Fadama Soils of

University Farm. Nigeria Journal of Basic and Applied sciences, 4, 29-30.

Smith, N., Smith, V., and Verner, M. (2006). Do women in top management affect firm performance? A

panel study of 2,500 Danish firms. International Journal of Productivity and Performance Management,

55(7), 569-593.

Tansey, G., and Worsley, A. (2014). The food system: Routledge.

UCHE, I. P. (2011). The Impact of Agricultural Policies on Nigerian Economy.

Umara, B. (2010). The State of Irrigation Development in Nigeria. Irrigation in West Africa: Current

Status and a View to the Future, 243.

Appendix I

Table 1: Fadama locations and their Areas in the irrigation Community L.G.A. VILLAGE/TOWN NAME OF FUA AREA(Ha) RESPONDENT

Badara Himma 372.55 3


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Badara Baba Baba 361.06 3

Guyaba - 225.78 3

Kirfi Kaffa 126.93 3

Kirfi Ramanu - 142.69 -

Wanka Himma 135.94 3

Boli Boli 113.36 3

Kafin-Iya Kafin Iya 100.48 3

Gaji - 81.69 - Alkaleri Maina Maji fanti Maina maji fanti 504.04 3

Duguri Himma fadama 124.20 1

association

Inkil Inkil multi-purpose 94.22 3

Bauchi cooperative

Lushi Lushi fadama 132.48 3

association

Bayara Bayara 144.93 3

Luda - 141.80 3

Bakin Rafin Zungur - 76.15 2

Juwara Juwara 291.56 3

T/Balewa Burga Burga 102.82 2

Gigyom - 24.53 -

Tafawa Balewa Tafawa Balewa 117.52 3

Zwall-shall Zwall 75.72 3

Gori Gori 172.55 3

Bogoro Kampani Kampani - 3

Doya Not registered 43.79 3

Wandi Mandak 162.69 3

Dass Durr Durr - 3

Dass III(Baraza) - 192.87 -

Dass II (Badel) - 187.26 -

Dass I (Dot) Alheri social club 399.17 3

Bauchi Bakin Kogin Zungur - 163.13 3

T/Balewa Dajin Sabon gari 111.20 3

Jajuwal Jajuwal 65.17 3

Toro Tudun wada Ribina Nil 30.62 3

Kogin sallah - 84.42 3

Zalau - 66.67 -

Riga - 4.99 -


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EXTENT AND CAUSES OF EUCALYPTUS TREE FARMING

EEXPANSION IN EZA WEREDA, ETHIOPIA

Corresponding Author: *Belay Zerga

Department of Natural Resources

Management , Wolkite University, Ethiopia.


Abstract

Land use/land cover change is a common phenomenon in all parts of the globe although with varying

magnitude. There are several possible causes for these changes, which may have economic, political or

social reasons. Eucalyptus tree farming has become the dominant activities next to growing enset in the

Gurage Zone in general and the study area, Eza wereda, in particular. The study assessed Extent and

causes of Eeucalyptus farming expansion in three selected KPAs (Kebele Peasant Administrations)

namely, Zigba Boto (kolla), Shebraden (woinadega) and Koter Gedra (dega). Here dega, woinadega, and

kolla represent temperate, subtropical and tropical climatic divisions respectively. In this study both

primary and secondary data were employed. Purposive systematic sampling procedure was used to select

the three agro-ecological areas of the wereda. In each selected KPAs 180 households were selected. Thus,

after selecting households with eucalyptus farms from the list of each KPA, every 5th

households were

interviewed. Direct observations, discussions with key informants and focus groups were undertaken by

the researcher. The required data were also collected using schedule through structured open and

close-ended questionnaires. Enset is a perennial herbaceous monocot and a staple food for more than

130,400 people in Eza wereda. These two dominant perennials grow together with other food crops such

as cereals, pulses, vegetable, fruits, and chat. The amount of eucalyptus woodlot generally increases with

farm size because farmers have better opportunities to grow more trees once they have satisfied their

subsistence and cash crop needs. In the study area eucalyptus tree plantation is a well-known emergent

and accelerating activity by small holder farmers. Eucalyptus is planted in the form of woodlots, farm

boundary, roads sides and around homesteads as a first priority tree species in the three sample Kebele

Peasant Administrations (KPAs). Eucalyptus trees are not found within croplands in these KPAs, which

could be the result of the fear of competition with agricultural corps, however, they are competing side by

side. Eucalyptus camaldulensis (red eucalyptus) grows in kolla and woina dega (but more in kolla zone),

while eucalyptus globules (white eucalyptus) grows more favorably in the woinadega and dega zones.

Key Words: Extent of eucalyptus tree expansion, causes of eucalyptus tree expansion, Land use land /land cover change,

Economic factors, Eza wereda

1. Introduction

Farm forestry is the integration of trees into farming systems though plantation, regeneration, or conservation forestry through

private initiative, either as part of crop production system or planned succession of field cropping system by trees with in the

farming system (EFAP, 1991; Tenaw, 2007).


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The environmental deterioration caused by combined effect of growing population and the pressure on the natural forests calls

for the need to establish plantation forests in tropical regions. Ethiopia is one of the countries badly struck by wide spread

decline of environmental stability and productivity due to a rapidly increasing population and long lasting deforestation. In

order to stop or slow down the deterioration, large sum of money and manpower have been invested to plant mainly fast

growing exotic tree species, mostly in connection with the establishment of plantations for the production of fuel wood. One

such exotic group is the eucalyptus, whose popularity, as plantation tree species is attributable to their being generally

adaptable, fast growing and with a wide range of productive and a variety of uses (Lisanework, 1994).

Livelihood is the way and means of making a living and it also is about creating and embracing new opportunities (Parrota et.

al., 2006). In financial terms, eucalyptus tree plantation yields substantial economic returns better than growing food crops

under many circumstances (Asaye, 2001; Tenaw, 2007). The mean annual increment of eucalyptus tree production is also

greater than many indigenous and exotic tree species. It is also hypothesized that farmers adopt tree plantation practices when

there are substantial economic incentives to do so at the regional and household level and as long as associated risks can be

managed (Selamyihun, 2004).

Small-holder farming practices in the tropics are faced with constant pressure of change brought about by demographic,

economic, technological and social pressures. Population growth, increasing commercialization of products and the use of

modern inputs are the most important factors that contributed to land use changes. In many tropical countries, agricultural land

use changed following the trajectory from hunter-gatherer life style in rain forests to market oriented mono-culture systems

resulting in increased higher per capita food supply at the global scale. Recently, concerns have developed on the long-term

sustainability and environmental consequences of the intensification of agricultural systems. Increasing attention is being given

to achieving stability in land utilization in the longer term while fulfilling the needs of the local population (Reijntjes et. al.,

1992; Swift and Ingram, 1996; Matson et. al., 2002).

Notably, in small holder farming systems in the tropics, the use of modern technologies might not be the first option to improve

agriculture. In such areas, better use of local resources and natural processes could make farming move effective and create

conditions for efficient, profitable, and safe use of modern inputs (Reijntjes et. al., 1992; Altieri, 1995).

Trees are integral components of most agricultural systems in the tropics playing vital roles in the livelihood of rural and urban

populations. They provide fuel wood, the major energy source in these areas, wood for construction and other purposes, and

their timber provides cash to many rural families (Fernandez and Nair, 1986; Long and Nair, 1999). With the rapid increase in

population, off- farm tree resources in most developing countries are becoming scarce and thus farmers manage trees on their

farms (Arnold and Dewees, 1995). The volume of wood in farms varies due to physical and socio-economic factors. For

instance, farmers with small land holding cannot have a large stock of trees since the available land is primarily used to

produce crops for consumption. Large holders on the other hand, could produce a large volume of wood (Sherr, 1995). A good

access to market could encourage farmers to engage in intensive management of trees for marketing (Gilmour, 1995).

Ethiopia has one of the longest forest plantation histories in Africa. To relieve the shortage of fuel wood caused by extensive

deforestation, eucalypts were introduced to the country in 1894-1895 (Pohjonen and Pukkala 1990). Eucalyptus globules were

the most successful of the 21-eucalypt species introduced and was quickly adopted by farmers. The reason for the wide-spread,

early popularity and success of the blue gum can be attributed to its fast growth, coppicing property, unpalatability of its leaves,

and adaptability to a wide range of site conditions (FAO, 1981b; Turnbull and Pryor, 1978). Various kinds of imperial


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incentives, such as tax relief for land planted with eucalypt trees and the distribution of seeds, have been important factors in

the spread of the tree in the early years (Horvath, 1968).

Forest plantations in Ethiopia were established essentially for fuel wood, and for industrial and environmental purposes, such

as soil conservation. The establishment of large-scale forest plantations planned primarily for fuel wood production was started

after the two global oil crises in the 1970s (Pohjonen, 1989). Most of these fuel wood plantations established after the oil crises

were funded by international organizations and owned by the state. Over 90% of the population uses biomass fuels for cooking,

heating and lighting (Mustanoja and Taye, 1990), and consequently, fuel wood is by far the major product of Ethiopian forests,

woodlands and trees on farms. For instance, in 1992 it consisted over 95% of the wood produced in the country (FAO, 1994).

Because of this prime importance of fuel wood to the society, forest plantations were established for fuel wood production

purposes. On the other hand, the share of industrial forest plantations was estimated to be 38% of the total plantation area in

the country (FAO, 2005).

According to Pohjonen and Pukkala (1990), in order to stop the deforestation of the remnant natural foresters, about 3-4

million hectares of firewood plantations were planned by the year 2000. However, the expansion of industrial and firewood

plantations was constrained by the availability of land and the limited capacity of the state bureaucracy to establish and operate

commercial forestry undertakings. Furthermore, government policies severely limited private sector activities in the forest

sector and this had detrimental effect on the expansion of forest plantations (EFAP, 1994).

2. Method of Data Collection

2.1 Location and Extent

The area of this study, Eza wereda is found in Gurage Zone of SNNPRS. The wereda (district) lies between 8003’ North to

8016’ North latitude and 37

0 50’ East to 38

0 12’ East longitude. Agena, the wereda main town is found 198 km and 42 km away

from Addis Ababa and Gurage Zone main town of Welkite respectively. The wereda is found in West Gurageland and bounded

by Cheha Wereda to the south, Muher and Aklil Wereda to the north, Abeshge and Kebena Weredas to the west, and Silte Zone

and Gumer Wereda to the east and southeast respectively (see Fig. 1).


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Figure 1 Location map of the study area

2.2 Research Methodology

2.2.1 Secondary Data:

To get clear understanding of the concept such as causes of eucalyptus farm forestry practices and land use land cover changes,

secondary data from journals, books and theses were reviewed.

2.2.2 Primary data:

W ERIT

GEDE B

AMBELI

KE TANE

YES RAY

SHEHRMO

SHAME NE

YAG UAJ TERE K

WADEY E

MENTER

W AS AMAR

NE SHE

KO KERAAMBA

GENE T

YEG

OB

ET

SNEBRADE N

BO ZEBAR

KOTER

GEDE RA

ZIGE BA

BOTO

GUYE NA

YES EWA

DARCHANAYEBARASA

WE RHE

AGE NADE SE NE

SABO LA

KE

RATE

MO

YAS HURANA

YE WARBIYA

SELLAM

M U H E R A N D A K L I L W E R E D A

AB

ESH

EGE

WE

RED

A

C H E

H A W

E R E D A

C H E H A W E R E D A

G U

M E

R

W E

R E

D A

S I

L T

E

Z O

N EN

EW

S

5 0 5 Kilom eters

OROMIA

SOM ALI

AMHA RA

AFAR

TIGRA Y

SOUTHE RN NAT IONS

NA TIONALITIES

AND PE OPLE S

BE NIS HANGUL

GUMZ

GAMB ELLA

DIRE DAW A

HARA RIADD IS AB EB A

SUDAN

SUDAN

KENYAKENYA

SOMALIA

SOMALIA

DJIBOUTI

ER ITREA

Regional B oundary

Zona l Boundary

W ereda Boundary

Study W ereda

LegendETHIOPIA

100 0 100 200 Kilom eters

Ke bele Bo und ary

Stud y KPAs

Le gend


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2.2.2.1 Data Collection Methods

To get primary data about the study purposive systematic sampling method was employed. Thus, after selecting households

with eucalyptus farms from the list of each KPA, questionnaires were distributed and asked to every 5th

households. The

questionnaires were distributed for sample households of the three KPAs agroecologically. To supplement the information,

discussions with focus groups and key informants were undertaken. Key informants and focus groups were:

� KPA (Kebele Peasant Administration) leaders;

� Wereda Office of Agriculture and Rural Development officials including DAs (Development Agents);

� Selected model and locally known farmers in eucalyptus tree farming;

� Wereda Water Desk officials.

2.2.2.2 Sampling Procedure, Size and Distribution

The study area, Eza wereda has 28 kebele Peasant Administrations (KPAs) with 130,487 populations (estimate of 2007). For

the purpose the study 3 KPAs were selected. The reason for selecting KPAs is that they represent agroclimatic zones of the

study area, eucalyptus tree farming is carried out more widely and they are more accessible to road transportation. The

surveyed KPAs were the following.

Table 1 Sample Size and Sampling Distribution

No. KPAs Agro-climatic

zone

Total population % No. of

Households

% No. of

sample

Households

%

1 Zigba Boto Kolla 2,749 27 514 27 50 27.8

2 Shebraden Woinadega 3,733 36 699 36 55 30.8

3 Koter Gedra Dega 3,882 37 727 37 75 41.7

Total 10364 100 1940 100 180 100

Source: Compiled from Eza wereda Administration Office, 2008 and EWIDP, 2007

As stated in table 1, from the selected three KPAs, 180 households were surveyed as unit of analysis. These households were

representatives of eucalyptus farming activities since eucalyptus growing and tenure system are more or less the same in the

wereda. The number of households interviewed were 50, 55, and 75 in kolla, woinadega and dega KPAs respectively. These

sample sizes were selected in relation to the extent of expansion.

2.2.2.3 Data Analysis

To analyze the various data collected, the study employed both qualitative and quantitative techniques. Qualitative techniques

were used to describe data acquired through observations, key informants, group discussions and questionnaires. The

quantitative data were analyzed using descriptive statistics (minimum and maximum percentage).

3. Extent of Eucalyptus tree Expansion

As a result of the dramatic expansion of eucalyptus particularly after 1980’s most households at least planted one hundred red or


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white or both types of tree species. Particularly eucalyptus planting has increased over the period of 1997 and 2001 in Eza wereda.

The increase in eucalyptus planting is attributable to price increment in eucalyptus poles. (See Table 2).

Table 2Eucalyptus trees planted by households for the last fifteen years in sample KPAs

Source: Household Survey (2008)

Sample households from the three agro climatic areas have clear understandings about the increment of their eucalyptus wood

lots from the adoption periods up to now. Planting more trees means creating varieties of opportunities in their livelihood. Thus,

as clearly indicated in Table 2, all respondents planted eucalyptus trees throughout those consecutive fifteen years. From the total

eucalyptus planted in those years 59%, 40% and 15% were planted in nearly flat or gently sloping topography of Zigba Boto,

Shebraden and Koter Gedra whereas 41%, 60% and 85% were planted in rugged areas respectively. Trends in the total area of

plantation indicate an increasing situation from 1980’s to 2007/08.

Muluneh (2003) in his study of West Gurageland on land use/land cover changes by using aerial photographs for two periods

(1957/71 and 1998), indicated considerable dynamics in the land use systems of six KPAs including the two KPAs in which this

study focuses (Shebraden and Koter Gedra). A total land use/land cover change in time span of 27 years for Koter Gedra

(1971-1998) and 41 years for Shebraden (1957-1998) were observed. Accordingly, eucalyptus tree plantation expansion showed

an increment of 169% for West Gurageland (six sample KPAs) including Shebraden and Koter Gedra.

Woodlands mainly eucalyptus trees showed the most dramatic expansion. Eucalyptus woodlots increased from 4.2%

(1957/67/71) to 11.2% (1998). Thus it showed an average expansion of about 169% as mentioned above in the last three to four

decades, though the recorded expansion in the six agro climatic areas ranged from about 100% in the woina dega KPAs to 169%

in the dega KPAs. Hence, the expansion was more important in the dega areas and accounted for about 42% in the aggregate

expansion while the woina dega and kolla KPAs contributed for about 34% and 26% respectively. Forest areas showed no

considerable changes probably due to the problems of interpretation and the scales of aerial photograph used. However, personal


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field observations showed marked determination, with considerable parts of Geche (Shebraden KPA’s possession) and Koter

Gedra (Koter Gedra KPA’s possession) forests thinned out by selective tree cutting and clearance for settlement. Thus, eucalyptus

expanded at the expense of others by way of transformation from one type of land unit to another or through modification.

However, at agro climatic zone level, the rate of conversion varied from about 71% in Koter Gedra (dega KPA). Out of the

observed changes, conversion from pastureland to eucalyptus wood lots (13%), shrubland to eucalyptus woodlots (7%) and

cropland to eucalyptus tree plantation (5.2%) were more important and accounted for about 46% of all transformations. The

expansion of eucalyptus plantations has been most important and competitive. Their expansion was largely at the expense of

grazing areas and to some extent to bush lands and croplands. The aforementioned land use/land cover change of the three sample

areas from 1957/71 to 1998 is shown in figure 2 to figure 5 below.

Figure 2-1957 Land use/Cover of Shebraden- Source: Muluneh (2003)


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Figure 3-1971 L and use/Cover of Koter Gedra- Source: Muluneh (2003)

Figure 4-1998 Land use/Cover of Shebraden - Source: Muluneh (2003)


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Figure 5-1998 Land use/Cover of Koter Gedra - Source: Muluneh (2003)

Table 3 Households’ perception on the trend of expansion of eucalyptus tree farming for the past consecutive years

(1980’s - 2008)

Response

Number of Respondents

Zigba Boto

%

Shebraden

%

Koter Gedra

%

Total

%

Increased 50 100 55 100 75 100 180 100

Decreased - - - - - - - -

No change - - - - - - - -

Total 50 100 55 100 75 100 180 100


As shown in Table 3, 100% of the respondents from all sample KPAs reported the dramatic trend of

expansion of eucalyptus tree plantation. The main reason as stated by respondents is that the role of

eucalyptus trees play in supporting households’ livelihood tend to excel the contribution generated

from other cash crops. However, some of the respondents reported that the fear eucalyptus trees

creates particularly in its competition with food crops such as enset and grazing lands is undeniable.


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Table 4 shows the beginning of adoption of eucalyptus in the three sample KPAs.

Table 4 The starting years of planting Eucalyptus trees

Years before

60

before

60-40

before

40-20

before

20-10

before

10-5

before

5-3

Total

Zigba Boto

No. of Respondents

7 15 21 5 2 - 50

% 14 30 42 10 4 - 100

Shebraden

No. of Respondents

9 17 21 6 2 - 55

% 16 31 38 11 4 - 100

Koter Gedra

No. of Respondents

12 27 27 9 - - 75

% 16 36 36 12 - - 100

Grand Total 28 59 69 20 4 - 180

% 16 33 38 11 2 - 100


As shown in Table 4, about 87% of the households started planting eucalyptus tree before 20 years; while about 13% of them

after 20 years. It appears then that the study region has had long experience of cropping eucalyptus trees.

4. Socio-Economic and Environmental Factors that Cause Eucalyptus Tree Farming Expansion

Population pressure and land use land cover change

Recently eucalyptus farm has rapidly expanded in West Gurageland. As noted by Muluneh (2003) the link between population

and environment, on the one hand, and population and the economy, on the other hand, are one of the most critically debated

issues. Many people consider that the most unfavorable changes in the environment and the economy of many pre-industrial

societies, most particularly degradation and poverty respectively, are the result of fast population growth. But there is a new

school of thought that views population growth, all other things remaining in a normal course of move, can induce innovation,

environmental recovery and, consequently, growth in the economy.

Although the area under study is less known for its environmental degradation like other weredas of Gurage Zone, small land

holders intensively practice eucalyptus tree farming as one means of conserving degraded areas particularly those of rugged areas.

As stated by Muluneh (2003) in West Gurageland including the study area; on individual basis, one peasant planted, on the


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average about 61 trees. Thereupon, eucalyptus plantation density increased by about 170% in the last four decades. This could

have partly contributed to the environmental recovery particularly in the degraded areas and justify the ''more people more tree

situation'', although it may be partly attributable to some other factors. At agroclimatic zone level, the rate of expansion varied

from 0.12% in kolla to 2.4% in woinadega and 7.3% per annum in dega. In addition to this population growth, of course together

with other factors such as improved access to road, town market and information has induced people to plant trees in degraded

areas and outside. These, therefore, serve for the purpose of environmental conservation and recovery. Muluneh (1994) in his

study revealed that the growing need of wood for construction and firewood, partly due to population growth, has been one of the

major drives to plant more eucalyptus trees. But the development of all season motorable road networks in the region since about

1960’s reported as one main factor in the expansion of eucalyptus tree farming at smallholder level. Hence, in order to fulfill

socio-economic needs, households preferred to plant more trees in their landholdings without taking some considerations to land

diminution which is the very serious issue in West Gurageland including the area of the study.

Table 5 Households’ Responses on whether Population Growth Facilitate Eucalyptus tree Expansion or Not

Response Number of Respondents Percentage

Zigba Boto

Yes 39 78

No 8 16

I don’t know 3 6

Total 50 100

Shebraden

Yes 49 89

No 6 11

I don’t know - -

Total 55 100

Koter Gedra

Yes 59 79

No 13 7

I don’t know 3 4

Total 75 100

Grand Total 180 100

Aggregate

Yes 147 82

No 27 15

I don’t know 6 3


Table 5 shows, of the total 180 respondents from the three sampled KPAs; 78%, 89% and 79% of the respondents believe that

expansion of eucalyptus tree farming has been due to population pressure in Zigba Boto, Shebraden and Koter Gedra respectively.

In aggregate 82% of them have the awareness that expansion of tree farming is in response to population increase. This may

partly substantiate the notion of “more people more tree”, particularly in fragmented and diminutive land holdings of the country.

Only about 15% of the respondents disagree with the situation. Their reason to this is that there is no more additional land due to


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its diminution. The remaining 3% of the respondents are not sure of such relationship.

Meskel Celebration and Fuel wood Consumption

Like other areas of the country, Meskel holiday/celebration has impacts on the socio-economic lives of Gurages. However, the

attachments of Gurages with Meskel is quite unique in terms of long duration of the celebration, cost, many number of returnee

people from domestic Diasporas and the like. The households start engaging with preparation for Meskel celebration before three

months. Among other things, fire wood is fetched well in advance before one to two months. Starting from June, i.e. before three

months of the celebration weak, each household begins to prepare fuel wood of higher quality. The best and readily available in

this regard is eucalyptus tree which is often used for this purpose. This has been the experience since the time of the eucalyptus

tree adoption. Discussions with an elder in Zigba Boto, noted that celebration of Meskel without fuel wood preparation, one may

not able to say I have celebrated Meskel in Gurage area in general and West Gurageland (Sebat Bet Gurageland) including the

study area in particular. The accumulation of splited eucalyptus logs are displayed in impressive arrangement in all “Guye Bet”

(big houses) of Gurages. After Meskel celebration, the remaining collected firewoods are used until end of October or in some

case until November and December.

Thus, for the prime reason of economic benefit, environmental recovery and social values such as Meskel, eucalyptus tree

farming is practiced with less attention to its negative ecological effects and land use competition. This is figurative when it is

compared to the number of Orthodox and Protestant Christianity followers which celebrate Meskel. As mentioned earlier, 86%

and 7% the respondents are flowers of Orthodox and Protestantism. Hence, collectively 93% of the respondents celebrate Meskel

and thereby use ample amount of eucalyptus fuel wood in the form of torch (‘demera’), for cooking food, heating and light.

Some KPA leaders such as Gizachew Bizani from Shebraden reported that farmers plant eucalyptus at least to fulfill fuel wood

for Meskel celebration if not for economic benefit. Generally speaking the wealthier the farmer is the more the amount of

eucalyptus fuel wood preparation is needed for Meskel. Therefore, eucalyptus trees remained part of Meskel celebration

requirements in Eza wereda similar to other Gurage regions in general and West Gurageland in particular and hence its expansion

will continue for such needs.

Land Degradation and Conservation

Population growth may not lead to environmental degradation if there is a reasonable amount of natural resource base, significant

access to internal and external markets, opportunities for non-farm income sources, active private trading network, fair social and

physical infrastructure, reasonable social and political stability, forward looking society and good governance (English, 1993;

cited in Muluneh, 2003). Muluneh (2003) in his study “population growth and Environmental recovery”, by supporting

Boserupian Theory, mentioned that, an increase in the destiny of population means that the number of people who can be served

from an individual location (other things being equal) increase; conversely, the cost of providing service to a given number of

people falls. At the same time the number of other individuals, with whom one person is likely to interact, will rise, which will

tend to increase the exchange of ideas and flow of information and increase the likelihood of new ideas and innovations being

generated. This in turn, will assist in solving the supply problems generated by population growth.

This, therefore encourage people to plant farm forestry such as eucalyptus trees in their degraded land holdings. Thus, in the area

of study, Eza wereda, like other weredas of Gurage Zone farmers practice conservation of their land to cope with the environment

since land diminution is a common problem. Such practice is done not for the sake of government plans and policies rather for


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survival in such limited landholding size. Table 6 indicates household response on conservation mechanisms through eucalypts

tree planting.

Table 6 Households’ Participation in Environmental Conservation through Eucalyptus tree planting

Response Number of Respondents Percentage

Zigba Boto

Yes 32 64

No 18 36

Total 50 100

Shebraden

Yes 40 73

No 15 27

Total 55 100

Koter Gedra

Yes 64 85

No 11 15

Total 75 100

Grand Total 180

Aggregate Yes 136 76

No 44 24


As indicated in Table 6, out of the total sample KPAs 64%, 73% and 85% of the respondents in Zigba Boto, Shebraden and Koter

Gedra respectively participated in environmental conservation by planting eucalyptus trees. In aggregate 76% of the respondents

use eucalyptus for conservation in degraded lands of households while 24% of them do not use such conservation practice. The

reason behind this, according to the respondents, is the fear of the adverse ecological effect of eucalyptus such as its high water

consumption, erosion, and soil nutrient depletion.

Road Development

Road development as one of the basic infrastructure has great role in the integration of economic, social, political and cultural

conditions of any country of low economic development like Ethiopia. As Muluneh (1994) stated the development of all-weather

roads in the Gurageland contributed to the land use/land cover change. As one of the factors of production, road stimulate farmers


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to plant cash crops which have high demand in the market. Due to nearness to Addis Ababa and other towns, the Gurage area in

general and the area of study in specific has great actual and potential advantages with regard to income diversification. Thanks

to the pioneers of road construction in West Gurageland, Gurage Road Construction Organization, almost every wereda has at

least one all-weather road, which links to the nearby markets and towns.

Eucalyptus poles, therefore, is transported by households using this road facilities. Particularly the kolla and woinadega farmers

are more beneficiaries due to the flat nature of the topography. Meaning, in dry seasons the purchasers can reach up to eucalyptus

woodlots without road networks since the terrain is not rugged. Therefore, Shebraden and Zigba Boto are more accessible than

Koter Gedra to reach eucalyptus woodlots even after the roads end up all weather and dry weather roads. That means in these

areas much man power is not needed to transport eucalyptus poles than the latter which transport from rugged areas to flat

surfaces in most cases. Thus, road development facilitated eucalyptus tree expansion in these areas.

Table 7 Households’ response on time spent from eucalyptus woodlots to the nearby roads (all weather roads and dry

whether roads) in minute

Time

Spent in minutes

All Weather

Road

%

Dry Weather Road

%

No. of

Respondents

No. of

Respondents

Zigba Boto

10-14 5 10 21 42

15-19 8 16 24 48

20-24 8 16 5 10

25-29 13 26 - -

30-34 16 32 - -

35-39 - - - -

Total 50 100 50 100

Shebraden

10-14 - - 8 14

15-19 - - 28 51

20-24 - - 17 31

25-29 4 7 2 4

30-34 19 35 - -

35-39 32 58 - -

Total 55 100 55 100

Koter Gedra

10-14 - 6 8

15-19 - 15 20

20-24 4 5 41 55

25-29 16 21 13 17


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30-34 33 44 - -

35-39 22 30 - -

Total 75 100 75 100

Grand Total 180 100 180 100

Aggregate

10-14 5 3 35 20

15-19 8 4 67 37

20-24 12 7 63 35

25-29 33 18 15 8

30-34 68 38 - -

35-39 54 30 - -


As depicted in table 7, the total time spent to reach dry weather roads is shorter for Zigba Boto than Shebraden and Koter Gedra.

All the sample respondents travel not more than 24 minutes to reach to dry weather road. People of Shebraden and Koter Gedra

reported that they travel up to 29 minutes. The reason why the travel time is too shorter for Zigba Boto is attributable to flat

topography. Vehicles can reach very close to eucalyptus woodlot areas without much difficulty. Distance traveled to all weather

roads by Zigba Boto households is also shorter than Shebraden and Koter Gedra. All the sample respondents in Zigba Boto travel

only 10 to 34 minutes while those of Shebraden and Koter Gedra travel up to 39 minutes to reach to all weather road network. In

aggregate 14% of the respondents travel 10 to 24 minutes and the other 86% travel 25 to 39 minutes to all weather roads.

However, 92% and 8% of them travel 10 to 24 and 25 to 39 minutes to dry weather roads respectively.

It appears that the development of motorable road transportation in the region has promoted farmers to plant more

eucalyptus trees. After they sell eucalyptus poles, of different sizes (small, medium, and big), they became motivated to plant

additional trees, and this has continued up to serious land use competition.

Increased Access to Markets

The sample KPAs of the study area are accessible to rural market places and towns. Agena the capital town of the wereda is about

15kms, 7kms and 20kms away from Koter Gedra, Shebraden and Zigba Boto. Poles can be transported using all weather roads to

the town in reasonably short time when farmers want to sell. On site sale of poles is also possible. Thus, farmers can sale their tree

plantation products either on site or transport into market place such as Agena, Welkite and Addis Ababa. Table 8 shows time

spent by households to travel the nearby towns.

Table 8 Time Spent from Households’ residence to the nearest town in minutes

Time Spent in

minutes

No. of Respondents Percentage

Zigba Boto

30-59 9 18

60-89 27 54


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90-119 14 28

Total 50 100

Shebraden

30-59 25 46

60-89 29 52

90-119 1 2

Total 55 100

Koter Gedra

30-59 56 75

60-89 19 25

90-119 - -

Total 75 100

Grand Total 180 100

Aggregate

30-59 90 50

60-89 75 42

90-119 15 8


As indicated in the Table 8, households from Koter Gedra have better access to the nearby town than Shebraden and Zigba Boto

since they travel in average 59 minutes. On the other hand respondents of Shebraden and Koter Gedra travel in average 74

minutes to reach the nearest town. Thus, eucalyptus poles of different types are sold to the town of their proximity. Shamene,

Agena and Gubre are the closest markets to Koter Gedra, Shebraden and Zigba Boto respectively. Middle men (‘Dellalas’)

provide assistance in creating links between woodlot sellers (farmers) and merchants. Therefore, improved access to market

places facilitated the expansion of eucalyptus tree farming in the study area.

Economic factors

Economic factors are by far the most important catalysts of eucalyptus tree plantation expansion in the study area and other areas

of Gurage Zone. With the growing trend of population pressure and degradation of natural forests farmers’ decision to plant fast

growing trees such as eucalyptus is unquestionable in the study area (which is one of the most densely populated areas of the

country). The main economic reasons for planting eucalyptus in the wereda include the growing need for fuel wood, construction,

and cash (money) for different purposes.


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The Growing Need for Fuel Wood: In rural areas biofuel has been the most important source of household energy. These sources

come mainly from firewood, crop residues and animal dung. Natural forests are rarely used as source of fire wood or else because

they are promoted natural balance and reduced environmental degradation. Thus, to cope with fuel wood demands at household

farmers started planting fast growing species mainly eucalyptus. The survey result showed that in Eza wereda, dependency on

natural forest for firewood has been shrinking because of the dramatic expansion of eucalyptus tree farming particularly to fulfill

domestic energy consumption. Animal dung and crop residues are good compliments of eucalyptus firewood particularly in

Koter Gedra than in Shebraden and Zigba Boto. In Shebraden and Zigba Boto, using animal dung was common before the

expansion of eucalyptus woodlots.

Table 9 Type of fuel wood energy used by households

Type of

Fuel

wood


Aggregate

Zigba Boto Shebraden Koter Gedra

Users %

Non

users

% Users %

Non

users

% Users %

Non

users

% Users %

Non

users

%

Eucalypt

us wood 50 100 - - 55 100 - - 75 100 - - 180 100 -

-

Animal

dung 21 42 29 58 6 11 49 89 68 91 7 9 95 53 85

47

Crop

residue 49 98 1 2 49 89 6 11 75 10 - - 173 96 7

4

From

forests 8 16 42 84 10 18 45 82 13 17 62 83 31 17 149

83


As shown in Table 9, eucalyptus wood is used by all the three KPAs’ respondents. Animal dung is used by 53% of the three

sample KPA households whereas non-users of it are 47%. This much reduction of using animal dung is probably attributable for

the wide adoption of eucalyptus tree farming by each household. Crop residues’ consumption by all the respondents is admirable

(96%) and encourageable since it has indirect advantage in reduction of deforestation and to some extent land use competition of

eucalyptus. Thus, the total consumption of eucalyptus in substituting the degraded natural forest is significant in the study area.


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Table 10 Experience of Households in using animal dung in the past

Response


Zigba Boto % Shebraden % Koter

Gedra

% Total %

Yes 37 74 44 80 75 100 156 87

No 13 26 11 20 - - 24 13

Total 50 100 55 100 75 100 180 100


From Table 10, it can be understood that in the past years 87% of the households were using animal dung as source of fuel

consumption. When it is compared to the present consumption (53%), there is reduction by 34%. The reason for such reduction

according to the respondents is due to the fact that animal manure is more useful when it is applied to enset farms and others as

fertilizer. The main reason to this is the availability of eucalyptus tree due to its dramatic expansion.

The Need for Construction: Before 20 years using eucalyptus as source of construction raw materials was less common

particularly in the woinadega and dega zones of the study area. The main sources of house construction materials were obtained

from own indigenous woodlots and natural forests. However, now a days because of the restriction of cutting of the existing

natural forests by government and the community at large and individual households in particular, farmers shifted their attention

to using fast growing trees such as eucalyptus. Previously junipers procera was the most preferred and defrosted plant for

construction. However, as a result of its slow growth nature, lack of availability and the very costly nature of the tree, its use for

construction purpose became less important. However, in woinadega areas, it is still used for construction proposes.

Particularly farmers prefer using eucalyptus camaldulensis (red eucalyptus) to eucalyptus globules (white eucalyptus) for

construction purposes as a result of its beauty and resistance to termites within the ground. The straight nature of red eucalyptus

is more conducive than the white one. The need of eucalyptus by farmers for construction purpose is totally accelerated. In

addition to house construction, eucalyptus tree has great role for fencing, making farm tools and local bridges.

Table 10 Households Multiple Response on Source of Wood for Construction

Sources



Gedra

% Total %

From own planted tree

(eucalyptus) 50 100 55 100

75 100

180 100

Buying form market and villages 26 52 51 100 70 93 147 82

Cutting from community forest - - - - - - - -


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Collecting from neighbors 45 90 55 100 68 91 168 93

From relatives and friends 42 84 55 100 71 95 93

Total 163 100 216 100 75 100 180 100


Table 10 shows that all the respondents from the three agro-ecological zones reported that they are using eucalyptus trees from

their own land holdings and 82% of them purchase from market or villagers. Farmers also collect contributions of trees from

neighbors, relatives and friends. According to the report all the households collect construction materials from this source as

noted above other than community plantation forests and natural forests. Most of these collected and purchased construction

woods are of eucalyptus tree and that is why, in addition to being source of fuel wood and money, eucalyptus trees became the

stable source of construction tools and other means of livelihood sustenance (support) of the households in the region. Thus, the

need for construction has its own impact for the expansion of eucalyptus trees in the area.

Growing Need for Cash (money): In the study area there is the need to rationalize the allocation of farm forestry and optimize

its use through competitive market economies to achieve maximum economic efficiency. It seems that cost and benefit from the

use of particularly eucalyptus trees is known by farmers. Eucalyptus tree for a given farmer means living bank account that can

be used when one is in need of money for different purposes such as to pay land or agricultural taxes, yearly celebrations like

Meskel and for supporting social institutions such as mahiber, weeding, zikir, ekub and idir. Even when a farmer needs to

cultivate own farmland one has to have enough money so as to pay for daily laborers and to purchase food items such as teff,

coffee, meat, drinks such as katikala and tela. The immediate source of money for all such expenses and others now a days partly

come from the sale of eucalyptus tree poles of different size (small, medium and big) in addition to selling cash crops such as

enset, chat, coffee, fruits, vegetables, cereals and pulses.

The author of this paper was well informed during household survey that some farmers in kolla (Zigba Boto) and woinadega

(Shebraden) collect about 35,000 ETB. in six years by selling eucalyptus poles, and logs. Such farmers are not only high prestige

ones because of their higher income but also socially more respected; and stated as model farmers by Woreda Agriculture and

Rural Development Office. Such farmers also motivated other peasants to plant more eucalyptus trees on their landholdings.

Table 11 Households’ Participation of Social Organizations in their Locality

Type of social organizations

Number of Respondents (Multiple response)


Gedra

% Total %

Idir 50 100 55 100

78 100

180 100

Ekub 26 52 21 38 48 64 95 53

Religious celebrations 50 100 55 100 75 100 180 100

Community meetings 50 100 55 100 75 100 180 100

Total 50 100 55 100 75 100 180 100


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All the sample KPAs’ respondents participate in all social organizations except in ‘ekub’ in which only 53% of the total

respondents take part (Table 11). Therefore, to take active part in all these social settings, cash generated from eucalyptus seems

has been very important. The income generated from selling eucalyptus woods supplements/compliments the household income

(livelihood support) obtained from crops, livestock and non-farm activities. Eucalyptus woodlots are also becoming strong

coping strategy of food security in addition to all others as reported by some farmers. Thus, many households have started

growing more trees, which ultimately accentuated expansion of eucalyptus tree plantations.

5. Conclusion

Land use/land cover change is a common phenomenon in all parts of the world. There are several possible

causes for land use/land cover changes. These might be economic, political, social or cultural reasons. In

the study area eucalyptus tree farming is becoming an important agricultural practice next to enset with

similar cases to other areas in the zone. The latter is a perennial monocot and a staple food for greater

than 130, 400 people in the region. Enset and eucalyptus trees are grown side by side with different crops

such as cereals, pulses, vegetables, fruits, chat, coffee and different types of trees and shrubs.

As a result, the dramatic expansion of eucalyptus tree farming increased from 1997 to 2008 due to

attractive market price of various types of poles (small, medium and big). The adoption of eucalyptus tree

farming has more than half century ages. Thus, 49% of the respondents started growing eucalyptus trees

before forty years and others (51%) after forty years. In the study area economic, social and

environmental factors contributed for the expansion of agroforestry in general and eucalyptus tree

farming in specific. Population pressure encouraged people to plant farm forestry such as eucalyptus in

different plantation sites as mentioned before. In dega and kolla KPAs farmland woodlots practices are

attributable to the flatness of the areas than the woinadega. Thus, land use competition between

eucalyptus tree and food crops is becoming stronger in these areas. On the other hand, road development

in the area initiated farmers to plant eucalyptus in flat areas, which are near to roadside.

Two ways of selling eucalyptus products is possible, i.e. to the nearby town (market); and to Addis Ababa

and other towns near to the area. Economic factors are the most important catalysts of eucalyptus tree

expansion so as to cope with fuel wood, construction and financial shortages for various social and

governmental duties. Before twenty or thirty years using eucalyptus as construction material was very

scanty particularly in woinadega areas of the study area. However, due to shortage of indigenous tree

products in farmers’ landholdings and markets, eucalyptus tree became the dominant source of

construction. The main reason to this is that eucalyptus is fast growing and ubiquitous than other farm

trees.

As key informants noted, eucalyptus for a given household means a living bank account that can be used

during shortage of money for different duties. The immediate source of money for all these expenses now

a days come from the sale of eucalyptus poles and logs in addition to food crops such as enset, vegetables,

cereals and pulses; and cash crops including chat and coffee. Thus, all the aforementioned causes

facilitated the rapid expansion of eucalyptus tree farming in Eza Wereda in specific and Gurage Zone in

general. Hence, to manage such rapid expansion of the species participatory community research and


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appropriate land use zoning/plan is needed. To combat environmental degradation and competition with

farmlands, closer and continuous awareness creation to smallholder farmers by wereda/district agriculture

and natural resource experts is also needed. This effort will sustain the ecology and livelihood of the

community.

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(Eds), Eucalyptus Wood Production. CSIRO, Adelaide, Australia pp. 6-66


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A STUDY ON APPLICATION OF NATURE INSPIRED ALGORITHMS

FOR SOLVING REACTIVE POWER PROBLEM

K. Lenin, Research Scholar, Dr. B.Ravindhranath Reddy, Dr. M.Surya Kalavathi

Abstract

Reactive power optimization problem has a substantial inspiration on secure and economic operation

of power system. This paper gives a detailed study on application Nature- Inspired algorithms to solve

Reactive Power Problem. Nature –Inspired Algorithms has been categorized as 1. Swarm Intelligence

Based Algorithms, 2.Bio- Inspired Algorithms, 3.Physics and Chemistry Based Algorithms. These

algorithms are so called based on the foundations of inspiration. By literature survey although not all of

them are efficient, many of the algorithms have been ascertained to be very competent and thus have

become popular tools for solving practical problems. This study reveals about the successful application

of the nature inspired algorithms to solve reactive power problem in both the modes of problem

formulation (single and multi-objective). The main aim of this study is to enhance the scholars around the

world to initiate them to work in the area of application of nature inspired algorithms to solve complex

power system problems.

Key words

Reactive power problem, Nature inspired algorithms, optimization

I. Introduction

Nature has been inspired by many researchers around the world in several means and thus is an ironic

foundation of stimulation for many inventions. In growing mode nature inspired algorithms utilized to

solve practical problems. Iztok Fister et al (2013) [1] given a brief review on nature inspired algorithms

for optimization and in detail author’s discussed about the classification of nature inspired algorithms and

explained about on what basis the classification has been done. In our (k.lenin, B.ravindranathreddy,

M.surya kalavathi) research we worked out application of nature inspired algorithm’s for solving

reactive power problem [2-39]. Various nature inspired algorithms as single algorithm and hybridized

algorithm utilized to solve the reactive power problem. In our research reactive power problem has been

formulated in two methods i) Optimal Reactive Power Dispatch problem including voltage stability

constraint problem is handled as a multi-objective optimization problem where both minimization of

power loss and maximum voltage stability margin of the system were optimized concurrently ,ii)Reactive

Power problem is handled as a single objective optimization problem where the minimization of the real

power loss is done along with the minimization of voltage deviations at load buses. All the three types of

nature inspired algorithms [2-39] have been used to solve reactive power problem in the above said two

forms of problem formulation. Also in our research[2-39] we kept the problem formulation (single and


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multi-objective) as standard one and to that various forms of nature inspired algorithms has been applied

and tested in standard IEEE 30, 57 and 118 bus system. Extensive comparison [2-39] has been made to

reveal about the successful application of the nature inspired algorithms.

II. Nature inspired algorithms application for solving reactive

power problem

In our (k.lenin, B.ravindranathreddy, M.surya kalavathi) research, these are the following nature

inspired algorithms has been applied to solve the reactive power problem in both the modes of problem

formulation. Ant Colony Search Algorithm [2], Spatial Extended Particle Swarm Optimization [3],

Attractive and Repulsive Particle Swarm Optimization [4], Intelligent Water Drop Algorithm [5], Fish

School Search Algorithm [6], Improved Teaching Learning Based Optimization [7], League

Championship Algorithm [8], Harmony Search Algorithm[9], Restarted Simulated Annealing Particle

Swarm Optimization [10], Adaptive bacterial foraging oriented particle swarm optimization algorithm

[11], Improved Great Deluge Algorithm [12], Improved Cuckoo Search Algorithm [13], Hybrid –

Invasive Weed Optimization Particle Swarm Optimization [14], Water Cycle Algorithm[15],Grand

salmon run algorithm [16], Dolphin Echolocation Algorithm[17], Black Hole Algorithm[18], Improved

Bees Algorithm [19], New charged system Search[20], Fusion of Flower Pollination Algorithm with

Particle Swarm Optimization[21], Improved Bat Algorithm[22], Hybrid Eagle Strategy Flower

Pollination Algorithm[23], Bumble Bees Mating Optimization[24], Mine Blast Algorithm[25], Improved

Spider Algorithm [26], Improved seeker optimization algorithm [27], Kudu Herd Algorithm[28], Double

Glow-Worms Swarm Co-Evolution Optimization Algorithm[29], Brain Storm Optimization

Algorithm[30], Crossbreed Spiral Dynamics Bacterial Chemotaxis Algorithm[31], Improved

Biogeography algorithm[32], Simulating Annealing Based Krill Herd Algorithm[33], Atmosphere Clouds

Model Algorithm[34], Adaptive Cat Swarm Optimization[35], Hybrid - Genetic Algorithm and

Hooke-Jeeves Method[36], Cuckoo Search Algorithm with Powell Search[37], Improved Evolutionary

Algorithm[38], Termite Colony Optimization[39] all these algorithms has been successfully applied to

solve the reactive power problem. Now around the world so many researchers are working in the area of

reactive power optimization problem. They are also utilized many nature inspired algorithms and other

innovative algorithms to solve the reactive power problem. K. Mahadevan et al (2010) [40]

Comprehensive learning particle swarm optimization for reactive power dispatch. Jaganathan et al (2011)

[41] applied Ant Colony Algorithm for Reactive Power Planning Problem. Pathak Smita et al (2012) [42]

solved Optimal Power Flow by Particle Swarm Optimization for Reactive Loss Minimization.

Chandragupta Mauryan et al (2012) [43] solved Reactive Power Optimization Using Quantum Particle

Swarm Optimization. R. Muthu Kumar et al (2012) [44] have solved swarm Based Identification and

Planning of Reactive Power in a Real Time System using Evolutionary Programming. J. V. Parate et al

(2012) [45] have solved Reactive Power Control and Transmission Loss Reduction. Kursat Ayan et al

(2012) [46] applied Artificial bee colony algorithm solution for solving optimal reactive power flow

problem. S. Duman et al (2012) [47] have solved optimal reactive power dispatch using a gravitational


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55

search algorithm. P. K. Roy et al (2012) [48] used biogeography based optimization for Optimal VAR

control for improvements in voltage profiles and for real power loss minimization. Santosh Kumar Morya

et al (2013) [49] solved Reactive Power Optimization Using Differential Evolution Algorithm. Amit

Saraswat et al (2013) [50] solved Multi-objective optimal reactive power dispatch considering voltage

stability in power systems using hybrid technique. B. Bhattacharyya et al (2013) [51] used Evolutionary

Techniques to solve reactive power problem. Phukan R et al (2013) [52] solved Reactive Power

Management using Firefly and Spiral Optimization under Static and Dynamic Loading Condition. Ting

Yu et al (2013) [53] have solved Multiple Dispatching Reactive Power and Voltage using Coordinated

Control Method. P.Surya kumara et al (2013) [54] used cat swarm algorithm for minimization of real

power loss. J.Jithendranath et al (2013) [55] used Differential Evolution approach for solving Optimal

Reactive Power Dispatch with Voltage Stability enhancement by Modal Analysis. Singh, H et al (2014)

[56] have solved combined active and reactive power dispatch using particle swarm optimization.

Mojtaba Shirvani et al (2014) [57] utilized Lagrangian method to solve the optimal power flow problem.

Mahalakshmi et al (2014) [58] utilized dynamic particle swarm optimization for solving optimal reactive

power problem. Yujiao Zeng et al (2014) [59] used hybrid multiobjective particle swarm optimization

algorithm to solve the optimal reactive power dispatch problem. Altaf Badar et al (2014) [60] used

improved AI techniques for solving optimal reactive power problem. K.R.Vadivelu et al (2014) [61]

utilized differential evolution method to solve reactive power planning problem. Tejaswini Sharma et al

(2014) [62] given detailed comparison between conventional and evolutionary methods for solving

reactive power problem. Amrane,Y et al (2014) [63] utilized particle swarm algorithm to solve

optimization problem. Zhuo Chenet al (2014) [64] had done Centralized Reactive Power Control for a

Wind Farm under Impact of Communication Delay. Govindaraj et al (2014) [65] had done Dynamic

Reactive Power Control of Islanded Micro grid. Arvindkumar et al (2014) [66] utilized differential

algorithm for solving reactive power problem. Andreas SPRING et al (2014) [67] had done grid voltage

influences of reactive power flows of photovoltaic inverters. SinaGhasempour et al (2014) [68] had done

Increase Productivity and Absorption of Reactive Power for Power Station with Using Static Reactive

Power Compensator. Ioulia T. Papaioannou et al (2014) [69] had done Reactive power consumption in

photovoltaic inverters. Bijaya Lubanjar et al (2014) [70] had done Fuzzy Logic based Reactive Power

Control System in Radial Feeder. Rahul Kumar Patel et al (2014) [71] had done Hybrid Active Power

Filters for Reactive Power Compensation with Adaptive DC-Link Voltage Control. Ming Zhu et al (2014)

[72] had done Dynamic Reactive Power Optimization Based on Genetic Algorithms in Power

Systems.Vadivelu et al (2014) [73] had done Soft Computing Technique Based Reactive Power Planning

using Combining Multi-objective Optimization with Improved Differential Evolution. Harinder Pal Singh

et al (2014) [74] had done Combined Active and Reactive Power Dispatch Using Particle Swarm

Optimization. Shahram Ahmadi et al (2014) [75] had done Separate control of active and reactive power

of Doubly-Fed Induction Generators (DFIG) Based on Wind Turbines at Unbalanced network Voltage

Conditions. Manohar et al (2014) [76] had done Reactive Power compensation using Series Pulse Voltage

Compensation for LCC HVDC at Offshore Wind Power. Stephyangelin et al (2014) [77] had done Active

and Reactive Power Pricing Considering Voltage Security. Mahalakshmi et al (2014) [78] had done Power


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System Reactive Power Optimization Using particle swarm optimization. This detailed study indicates to

us many of the nature inspired algorithms very successfully handled the reactive power problem. And

huge hope has been emerging out to utilize nature inspired algorithms for solving other power system

problems.

III. Conclusion

Detailed study has been conducted on application of nature inspired algorithm for solving reactive power

problem. Form the study it’s very clear that nature inspired algorithms is capable of handling the reactive

power problem in best mode. Many researchers around the world utilizing various types of nature

inspired algorithms for solving real time problems. Almost all areas in the engineering field nature

inspired algorithms emerge as front runner to handle the difficult problems. Also this study enhances us to

move forward for the application of nature inspired algorithms to solve other complex problems in power

system operation and control.

References

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