Solar radiation estimation using aritificial neural networks

Atsu S.S. Dorvlo*, Joseph A. Jervase, Ali Al-Lawati

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

231 اقتباسات (Scopus)

ملخص

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.

اللغة الأصليةEnglish
الصفحات (من إلى)307-319
عدد الصفحات13
دوريةApplied Energy
مستوى الصوت71
رقم الإصدار4
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2002

ASJC Scopus subject areas

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  • ???subjectarea.asjc.2100.2100???
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