干旱区生态环境知识资源中心(Arid): Estimation method for ET0 with PSO-LSSVM based on the HHT in cold and arid data-sparse area

Arid

DOI	10.1007/s10586-018-1726-x
	Estimation method for ET0 with PSO-LSSVM based on the HHT in cold and arid data-sparse area
	Wang, Pengxiang; Liu, Chang; Li, Yunkai
通讯作者	Li, YK (corresponding author), China Agr Univ, Coll Water Resources & Civil Engn, Beijing 100083, Peoples R China.
来源期刊	CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
ISSN	1386-7857
EISSN	1573-7543
出版年	2019
卷号	22 页码:S8207-S8216
英文摘要	A coupled particle swarm optimization (PSO) least squares support vector machine (LSSVM) model based on the Hilbert-Huang transform (HHT) was established to provide accurate estimations of reference crop evapotranspiration (ET0) in cold and arid areas that lack the required meteorological data. Daily data (2000-2009) from the Hetian Xinjiang meteorological station (China) were used for training and double-day data used for validation. The accuracy of the method was compared with two machine models, the conventional PSO-LSSVM model and a generalized regression neural network, and three empirical methods, the Hargreaves, FAO-24 Penman, and Priestley-Taylor models. Under the condition of the same parameters of meteorological data, the accuracies of the machine models were found better than the empirical models, and the precision of the PSO-LSSVM coupled algorithm based on the HHT was the highest. The relative importance of the prediction elements was Rs > Tmax > Tmin > RH > Wn. When the deletion combination was Tmax/Tmin/RH/Wn, Tmax/RH/Wn, Tmin/Wn, and Wn, the mean square error was 0.407, 0.185, 0.149, 0.135, respectively, which shows this method is adequate for estimating ET0 in data-sparse areas.
英文关键词	Reference crop evapotranspiration (ET0) HHT PSO-LSSVM Prediction model
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000502007000052
WOS关键词	REFERENCE EVAPOTRANSPIRATION
WOS类目	Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS研究方向	Computer Science
来源机构	中国农业大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/369933
作者单位	[Wang, Pengxiang; Liu, Chang; Li, Yunkai] China Agr Univ, Coll Water Resources & Civil Engn, Beijing 100083, Peoples R China
推荐引用方式 GB/T 7714	Wang, Pengxiang,Liu, Chang,Li, Yunkai. Estimation method for ET0 with PSO-LSSVM based on the HHT in cold and arid data-sparse area[J]. 中国农业大学,2019,22:S8207-S8216.
APA	Wang, Pengxiang,Liu, Chang,&Li, Yunkai.(2019).Estimation method for ET0 with PSO-LSSVM based on the HHT in cold and arid data-sparse area.CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS,22,S8207-S8216.
MLA	Wang, Pengxiang,et al."Estimation method for ET0 with PSO-LSSVM based on the HHT in cold and arid data-sparse area".CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 22(2019):S8207-S8216.