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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
	Fan, Junliang; Wu, Lifeng; Zhang, Fucang; Cai, Huanjie; Zeng, Wenzhi; Wang, Xiukang; Zou, Haiyang
刊名	RENEWABLE & SUSTAINABLE ENERGY REVIEWS
	2019
卷号	100
关键词	Solar radiation Machine learning Model comparison Global performance index (GPI) Computational time Memory usage
ISSN号	1364-0321
DOI	10.1016/j.rser.2018.10.018
URL标识	查看原文
收录类别	SCIE
语种	英语
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/4217154
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[J]. RENEWABLE & 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.RENEWABLE & 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".RENEWABLE & SUSTAINABLE ENERGY REVIEWS 100(2019).

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