Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure

Kasra Mohammadi, Shahaboddin Shamshir , Amirrudin Kamsin , Lai, P.C., Zulkefli Mansor

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Type :	Academic Journal
Main Author :	Kasra Mohammadi, Shahaboddin Shamshir , Amirrudin Kamsin , Lai, P.C., Zulkefli Mansor
Title :	Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure
Varying Form of Title :	Renewable and Sustainable Energy Reviews 63, 2016, pages 423–434
Content Type :	still image (rdacontent)
Media Type :	computer (rdamedia)
Carrier Type :	online resource (rdacarrier)

Place of Production :	Kuala Lumpur
Publisher :	Renewable and Sustainable Energy Reviews
Year of Publication :	2016
Summary :	There are several variables that influence the global solarradiation (GSR) prediction; thus, determining the most significant parameterss an important task to achieve accurate predictions. In this paper, adaptive neuro fuzzy inference system (ANFIS) is employed to identify the most relevant parameters for prediction of daily GSR. Three cities of Isfahan, Kerman and Tabass distributed in central and south central parts of Iran are considered as case studies.
Corporate Name :	UNIRAZAK Library
PDF Guest :	Click to view PDF file

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