Title of article
Solar radiation estimation using artificial neural networks
Author/Authors
Atsu S. S. Dorvlo، نويسنده , , Joseph A. Jervase، نويسنده , , Ali Al-Lawati، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2002
Pages
13
From page
307
To page
319
Abstract
Artificial Neural Network Methods are discussed for estimating solar radiation by first estimating the clearness index. Radial Basis Functions, RBF, and Multilayer Perceptron, MLP, models have been investigated using long-term data from eight stations in Oman. It is shown that both the RBF and MLP models performed well based on the root-mean-square error between the observed and estimated solar radiations. However, the RBF models are preferred since they require less computing power. The RBF model, obtained by training with data from the meteorological stations at Masirah, Salalah, Seeb, Sur, Fahud and Sohar, and testing with those from Buraimi and Marmul, was the best. This model can be used to estimate the solar radiation at any location in Oman.
Keywords
Radial basis functions , Solar radiation , Clearness index , Artificial neural networks
Journal title
Applied Energy
Serial Year
2002
Journal title
Applied Energy
Record number
414357
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