气候变化领域集成服务门户(CCPortal): Objective approach for rainstorm based on dual-factor feature extraction and generalized regression neural network

CCPortal

DOI	10.1007/s11069-020-04258-4
	Objective approach for rainstorm based on dual-factor feature extraction and generalized regression neural network
	Xiaoyan H.; Li H.; Huasheng Z.; Ying H.; Yushuang W.
发表日期	2020
ISSN	0921030X
起始页码	1987
结束页码	2002
卷号	104 期号:3
英文摘要	Rainstorm often causes inland flooding and mudslides that threaten lives and properties. In this study, rainstorm is used as a forecasting object, and an interpretation prediction model for rainstorm based on the European Center for medium-range weather forecasting (ECMWF) numerical prediction model is constructed through the generalized regression neural network method. Model inputs are forecasted through principal component analysis, and dual-factor feature extraction is performed on the primary predictors to obtain new irrelevant variables and optimize network structures. The experimental forecast results of the 24 h aging test using an independent sample of large-scale rainstorm in Guangxi, China from 2012 to 2016, the actual forecast results of selected rainstorm cases with great influence on Guangxi, and different influencing systems show that the new prediction scheme is sophisticated. Thus, the scheme has a certain universal applicability. The results of the comparative analysis between the new program and ECMWF show that the forecasting ability of the new method is more accurate than that of the direct numerical forecasting model. The threat score of the new forecast model for 5 years has a 58.4% increase relative to that of the ECMWF. The forecasting skills are positive and good and can thus improve the rainstorm forecasting ability of ECMWF and provide a better guidance for forecasters. © 2020, Springer Nature B.V.
关键词	Dual-factor feature extraction Generalized regression neural network (GRNN)Kernel principal component analysis (KPCA)Rainstorm
英文关键词	artificial neural network; numerical model; pattern recognition; principal component analysis; rainstorm; regression analysis; weather forecasting; China; Europe; Guangxi Zhuangzu
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206007
作者单位	Guangxi Institute of Meteorological Science, Nanning China, 81 National Road, Nanning, 530022, China
推荐引用方式 GB/T 7714	Xiaoyan H.,Li H.,Huasheng Z.,et al. Objective approach for rainstorm based on dual-factor feature extraction and generalized regression neural network[J],2020,104(3).
APA	Xiaoyan H.,Li H.,Huasheng Z.,Ying H.,&Yushuang W..(2020).Objective approach for rainstorm based on dual-factor feature extraction and generalized regression neural network.Natural Hazards,104(3).
MLA	Xiaoyan H.,et al."Objective approach for rainstorm based on dual-factor feature extraction and generalized regression neural network".Natural Hazards 104.3(2020).