(0200) “Radial Basis Functions Neural Networks for Estimation of Global Solar Radiation”. Journal of International Solar Energy, 68 (2). pp. 161-168.

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Abstract

The present study utilizes the radial basis functions technique for the estimation of monthly mean daily values of solar radiation falling on horizontal surfaces and compares its performance with that of the multilayer perceptrons network and a classical regression model. In this work, we use solar radiation data from 41 stations that are spread over the Kingdom of Saudi Arabia. The solar radiation data from 31 locations are used for training the neural networks and the data from the remaining 10 locations are used for testing the estimated values. However, the testing data were not used in the modeling or training of the networks to give an indication of the performance of the system at unknown locations. Results indicate the viability of the radial basis for this kind of problem.

Item Type:	Article
Subjects:	Electrical
Department:	College of Engineering and Physics > Electrical Engineering
Depositing User:	AYHAM ZAZA
Date Deposited:	12 Apr 2008 10:13
Last Modified:	01 Nov 2019 13:26
URI:	http://eprints.kfupm.edu.sa/id/eprint/1104