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“Radial Basis Functions Neural Networks for Estimation of Global Solar Radiation”

Balghonaim, Adil S. (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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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
Date:February 0200
Divisions:College Of Engineering Sciences > Electrical Engineering Dept
Creators:Balghonaim, Adil S.
ID Code:1104
Deposited By:AYHAM ZAZA
Deposited On:12 Apr 2008 13:13
Last Modified:12 Apr 2011 13:09

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