The present study utilizes the radial basis functions technique for the est
imation of monthly mean daily values of solar radiation falling on horizont
al surfaces and compares its performance with that of the multilayer percep
trons 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 A
rabia. 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 th
e modeling or training of the networks to give an indication of the perform
ance of the system at unknown locations. Results indicate the viability of
the radial basis for this kind of problem. (C) 2000 Elsevier Science Ltd. A
ll rights reserved.