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100			_aShaban G Gouda _958526
245			_aReview of empirical solar radiation models for estimating global solar radiation of various climate zones of China/
260			_bSgae, _c2020.
300			_aVol 44, issue 2, 2020 : ( 168–188 p.).
520			_aUtilizing solar energy requires accurate information about global solar radiation (GSR), which is critical for designers and manufacturers of solar energy systems and equipment. This study aims to examine the literature gaps by evaluating recent predictive models and categorizing them into various groups depending on the input parameters, and comprehensively collect the methods for classifying China into solar zones. The selected groups of models include those that use sunshine duration, temperature, dew-point temperature, precipitation, fog, cloud cover, day of the year, and different meteorological parameters (complex models). 220 empirical models are analyzed for estimating the GSR on a horizontal surface in China. Additionally, the most accurate models from the literature are summarized for 115 locations in China and are distributed into the above categories with the corresponding solar zone; the ideal models from each category and each solar zone are identified. Comments on two important temperature-based models that are presented in this work can help the researchers and readers to be unconfused when reading the literature of these models and cite them in a correct method in future studies. Machine learning techniques exhibit performance GSR estimation better than empirical models; however, the computational cost and complexity should be considered at choosing and applying these techniques. The models and model categories in this study, according to the key input parameters at the corresponding location and solar zone, are helpful to researchers as well as to designers and engineers of solar energy systems and equipment.
700			_aHussein, Zakia _958527
700			_aLuo, Shuai _958528
700			_aYuan, Qiaoxia _958529
773	0		_012665 _917140 _dLondon: Sage Publication Ltd, 2019. _tProgress in Physical Geography: Earth and Environment/ _x03091333
856			_uhttps://doi.org/10.1177/0309133319867213
942			_2ddc _cEJR
999			_c14906 _d14906