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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Comparative Study of Fuzzy System and Artificial Neural Networks in Predicting Solar Radiation in Tehran Province

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Author Zeynab Ramedani, Mahmoud Omid, Alireza Keyhani
ISSN 2079-8407
On Pages 409-416
Volume No. 4
Issue No. 4
Issue Date May 01, 2013
Publishing Date May 01, 2013
Keywords Solar radiation; prediction; artificial neural network; neuron-fuzzy system.


Abstract

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.
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