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Artificial neural network ensembles in time series forecasting: an application of rainfall forecasting in Sri Lanka

Authors:

Harshani R. K. Nagahamulla ,

Wayamba University of Sri Lanka, Kuliyapitiya, Sri Lanka, LK
About Harshani
Dept of Computing & Information Systems, Faculty of Applied Sciences
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Uditha R. Ratnayake,

University of Peradeniya Peradeniya, Sri Lanka, LK
About Uditha
Dept of Civil Engineering, Faculty of Engineering
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Asanga Ratnaweera

University of Peradeniya Peradeniya, Sri Lanka, LK
About Asanga
Dept of Mechanical Engineering, Faculty of Engineering
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Abstract

Weather forecasting is a widely researched area in time series forecasting due to the necessity of accurate weather forecasts in various human activities. Out of numerous weather forecasting techniques Artificial Neural Networks (ANN) methodology is one of the most widely used techniques. In this study the application of Neural Network Ensembles in Rainfall Forecasting is investigated by using various types of Ensemble Neural Networks (ENN) to forecast the rainfall in Colombo, Sri Lanka. Ensembles are generated by changing the network architecture, changing initial weights of the ANN and changing the ANN type. Two ensembles one consisting of a collection of networks of various architectures of Multi Layer Feed Forward Network with Back Propagation Algorithm (BPN), and the other consisting of a combination of BPN, Radial Basis Function Network (RBFN) and General Regression Neural Network (GRNN). The performance of ensembles are compared with the performance of BPN, RBFN and GRNN. The ANNs are trained, validated and tested using daily observed weather data for 41 years. The results of our experiment show that the performance of the ensemble models are better than the performance of the other models for this application and that changing the network type gives better results than changing the architecture of the ANN.

DOI: http://dx.doi.org/10.4038/icter.v6i2.7151

International Journal on Advances in ICT for Emerging Regions (ICTer), 2013;v.6(2)

How to Cite: Nagahamulla, H.R.K., Ratnayake, U.R. & Ratnaweera, A., (2014). Artificial neural network ensembles in time series forecasting: an application of rainfall forecasting in Sri Lanka. International Journal on Advances in ICT for Emerging Regions (ICTer). 6(2). DOI: http://doi.org/10.4038/icter.v6i2.7151
Published on 16 Jul 2014.
Peer Reviewed

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