Radial basis function neural networks model to estimate global solar radiation in semi-arid area
Journal Title: Leonardo Electronic Journal of Practices and Technologies - Year 2015, Vol 14, Issue 27
Abstract
For many developing countries, solar radiation measurements are only available for selected stations due to the cost of the measurement equipment and techniques involved. In this study, a simple model based on Radial Basis Function neural networks is proposed to estimate the Daily Global Solar Radiation using a limited meteorological data measured at Ghardaïa station. The study covered three years from 2012 (1st January) to 2014 (28th October). The obtained results show that the Radial Basis Function neural network model predicts the Daily Global Solar Radiation of clear and perturbed days with a good accuracy. The difference between the measured and the predicted values show a Root Mean Square Error of 0.014.
Authors and Affiliations
RABEHI Abdelaziz , GUERMOUI Mawloud , DJAFER Djelloul , ZAIANI Mohamed
Keywords
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