Intelligent Database Systems Lab

Presenter : Kung, Chien-Hao

Authors : Medhdi Khashei, Mehdi Bijari

2011, ASOC

A novel hybridization of artificial neural networks and ARIMA models

for time series forecasting

Intelligent Database Systems Lab

Outlines

MotivationObjectivesMethodologyExperimentsConclusionsComments

Intelligent Database Systems Lab

Motivation• Artificial neural networks(ANNs) are applied

to a wide range of forecasting problems.

• However, using ANNs to model linear problems

have yielded mixed results, and hence; it’s not wise

to apply ANNs blindly to any type of data.

Intelligent Database Systems Lab

Objectives• To overcome limitation of ANNs and yield more

general and more accurate forecasting model.

Intelligent Database Systems Lab

Methodology-Framework

ARIMA

ANNs

Forecast

Intelligent Database Systems Lab

Methodology

ARIMA

ANNs

Forecast

AR MA

ARMA

ARIMA

Intelligent Database Systems Lab

Methodology

ARIMA

ANNs

Forecast

Intelligent Database Systems Lab

Methodology

ARIMA

ANNs

Forecast

Intelligent Database Systems Lab

Experiments-Sunspot dataset

Intelligent Database Systems Lab

Experiments-Lynx dataset

Intelligent Database Systems Lab

Experiments-Exchange rate dataset

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Conclusions

• A novel hybridization of ANNs and ARIMA model is

proposed in order to overcome the limitation of ANNs

and yield the more general and the more accurate

forecasting model.

Intelligent Database Systems Lab

Comments• Advantages– The experiment is rich.

• Applications– Time series forecasting.