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	Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China (Open Access)
	Fan, Junliang; Wu, Lifeng; Zhang, Fucang; Cai, Huanjie; Zeng, Wenzhi; Wang, Xiukang; Zou, Haiyang
刊名	Renewable and Sustainable Energy Reviews
	2019
卷号	100
ISSN号	1364-0321
DOI	10.1016/j.rser.2018.10.018
URL标识	查看原文
收录类别	EI
语种	英语
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/4233165
专题	武汉大学
推荐引用方式 GB/T 7714	Fan, Junliang,Wu, Lifeng,Zhang, Fucang,et al. Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China (Open Access)[J]. Renewable and Sustainable Energy Reviews,2019,100.
APA	Fan, Junliang.,Wu, Lifeng.,Zhang, Fucang.,Cai, Huanjie.,Zeng, Wenzhi.,...&Zou, Haiyang.(2019).Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China (Open Access).Renewable and Sustainable Energy Reviews,100.
MLA	Fan, Junliang,et al."Empirical and machine learning models for predicting daily global solar radiation from sunshine duration: A review and case study in China (Open Access)".Renewable and Sustainable Energy Reviews 100(2019).

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