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 Motivation Objectives Methodology Experiments Conclusions Comments

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 MAARMAARIMA

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.