期刊名称：Journal of Emerging Trends in Computing and Information Sciences
电子版ISSN：2079-8407
出版年度：2013
卷号：4
期号：4
页码：409-416
出版社：ARPN Publishers
摘要：In this study, artificial neural networks (ANN) and Adaptive-Network-Base fuzzy inference system (ANFIS) are used to model daily global solar radiation (GSR) in Tehran province of Iran. In order to design the networks, a dataset of meteorological daily time series for eight years (1994-2002) collected by Iran Meteorological Office was used. Input parameters were maximum temperature, relative sunshine duration, day of the year and extraterrestrial solar radiation while the output parameter was the GSR in MJ/m2 day. Various networks were designed and tested. The performances of best networks revealed that RMSE, MAE and MAPE were 2.77, 2.19, 0.12 for ANN and 2.8, 2.22, 0.12 for ANFIS, respectively. The results indicated that both approaches can be successfully applied for modeling GSR however ANN performs slightly better.
