气候变化领域集成服务门户(CCPortal): Stepwise extreme learning machine for statistical downscaling of daily maximum and minimum temperature

CCPortal

DOI	10.1007/s00477-019-01680-4
	Stepwise extreme learning machine for statistical downscaling of daily maximum and minimum temperature
	MoradiKhaneghahi, Mahsa; Lee, Taesam; Singh, Vijay P.
发表日期	2019-06-01
ISSN	1436-3240
EISSN	1436-3259
卷号	33 期号:4-6 页码:1035-1056
英文摘要	Increasing temperature from climate change can bring a number of different risks such as more droughts and heat waves, and increasing sea level rise. Assessment of climate change with future scenarios is essential to adapt these impacts. To provide climat
关键词	Artificial neural network Extreme learning machine Feature selection Stepwise Temperature downscaling
学科领域	Engineering, Environmental;Engineering, Civil;Environmental Sciences;Statistics & Probability;Water Resources
语种	英语
WOS记录号	WOS:000472942200006
来源期刊	STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/80960
作者单位	Gyeongsang Natl Univ, Dept Civil Engn, ERI, 501 Jinju Daero, Jinju 660701, Gyeongnam, South Korea
推荐引用方式 GB/T 7714	MoradiKhaneghahi, Mahsa,Lee, Taesam,Singh, Vijay P.. Stepwise extreme learning machine for statistical downscaling of daily maximum and minimum temperature[J],2019,33(4-6):1035-1056.
APA	MoradiKhaneghahi, Mahsa,Lee, Taesam,&Singh, Vijay P..(2019).Stepwise extreme learning machine for statistical downscaling of daily maximum and minimum temperature.STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,33(4-6),1035-1056.
MLA	MoradiKhaneghahi, Mahsa,et al."Stepwise extreme learning machine for statistical downscaling of daily maximum and minimum temperature".STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 33.4-6(2019):1035-1056.