Temperature forecasting with a dynamic higher-order neural network model

Authors:
Noor Aida Husaini;Rozaida Ghazali;Lokman Hakim Ismail;Norhamreeza Abdul Hamid;Mustafa Mat Deris;Nazri Mohd Nawi
Affiliations:
UTHM Malaysia, Bt. Pahat, Johor, Malaysia;UTHM Malaysia, Bt. Pahat, Johor, Malaysia;UTHM Malaysia, Bt. Pahat, Johor, Malaysia;UTHM Malaysia, Bt. Pahat, Johor, Malaysia;UTHM Malaysia, Bt. Pahat, Johor, Malaysia;UTHM Malaysia, Bt. Pahat, Johor, Malaysia
Venue:
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Year:
2011

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Abstract

This paper presents the application of a combined approach of Higher Order Neural Networks and Recurrent Neural Networks, so called Jordan Pi-Sigma Neural Network (JPSN) for comprehensive temperature forecasting. In the present study, one-step-ahead forecasts are made for daily temperature measurement, by using a 5-year historical temperature measurement data. We also examine the effects of network parameters viz the learning factors, the higher order terms and the number of neurons in the input layer for selecting the best network architecture, using several performance measures. The comparison results show that the JPSN model can provide excellent fit and forecasts with reasonable results, therefore can be used as temperature forecasting tool.