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An optimal higher order for Jordan Pi-Sigma neural network on temperature forecasting

Husaini, Noor Aida and Ghazali, Rozaida and Mohd Nawi, Nazri and Ismail, Lokman Hakim (2011) An optimal higher order for Jordan Pi-Sigma neural network on temperature forecasting. In: 2nd World Congress on Information Technology (WCIT-2011), 23-26 November 2011, Antalya, Turkey.

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This paper presents an optimal higher order to forecast temperature event in Batu Pahat, Malaysia by using a Jordan Pi-Sigma Neural Network (JPSN). There are many conventional techniques in dealing with forecasting meteorological issue, however, there are some shortcoming noticed in terms of accuracy and tractability. The data of temperature measurement in Batu Pahat has been used in order to validate the network model by utilizing the backpropagation training algorithm. The results of the prediction made by JPSN were compared with the widely known Multilayer Perceptron Towards the end, we found that the JPSN of Order 2 gives best results in predicting the next-day ahead prediction, thus can be used for temperature forecasting with acceptable lower prediction error.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: temperature forecasting; prediction; Jordan Pi-Sigma; multilayer perception; neural network
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 31 Jan 2013 08:04
Last Modified: 21 Jan 2015 07:13
URI: http://eprints.uthm.edu.my/id/eprint/2955
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