期刊名称：Journal of Sustainable Development of Energy, Water and Environment Systems
电子版ISSN：1848-9257
出版年度：2018
卷号：6
期号：3
页码：405-414
DOI：10.13044/j.sdewes.d6.0226
语种：English
出版社：International Centre for Sustainable Developmen of Energy, Water and Environment Systems
摘要：This work deals with the potential application of artificial neural networks to model sunshine duration in three cities in Algeria using ten input parameters. These latter are: year and month, longitude, latitude and altitude of the site, minimum, mean and maximum air temperature, wind speed and relative humidity. They were selected according to their availability in meteorological stations and based on the fact that they are considered as the most used parameters by researchers to model sunshine duration using artificial neural networks. Several network architectures were tested to choose the most accurate and simple scheme. The optimum number of layers and neurons was determined by trial and error method. The optimized network was obtained using Levenberg-Marquardt back-propagation algorithm, one hidden layer including 25 neurons with Tan-sigmoid transfer function. The model developed in this study has the ability to estimate sunshine duration with a mean absolute percentage error value equals to 2.015%, a percentage root mean square error of 2.741% and a determination coefficient of 0.9993 during test stage.
关键词：Sunshine duration; Solar energy; Artificial neural networks; Root mean square error; Meteorological parameters.
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