干旱区生态环境知识资源中心(Arid): Applicability of epsilon-Support Vector Machine and Artificial Neural Network for Flood Forecasting in Humid, Semi-Humid and Semi-Arid Basins in China

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DOI	10.3390/w11010085
	Applicability of epsilon-Support Vector Machine and Artificial Neural Network for Flood Forecasting in Humid, Semi-Humid and Semi-Arid Basins in China
	Bafitlhile, Thabo Michael; Li, Zhijia
通讯作者	Bafitlhile, Thabo Michael
来源期刊	WATER
ISSN	2073-4441
出版年	2019
卷号	11 期号:1
英文摘要	The aim of this study was to develop hydrological models that can represent different geo-climatic system, namely: humid, semi-humid and semi-arid systems, in China. Humid and semi-humid areas suffer from frequent flood events, whereas semi-arid areas suffer from flash floods because of urbanization and climate change, which contribute to an increase in runoff. This study applied -Support Vector Machine (epsilon-SVM) and artificial neural network (ANN) for the simulation and forecasting streamflow of three different catchments. The Evolutionary Strategy (ES) optimization method was used to optimize the ANN and SVM sensitive parameters. The relative performance of the two models was compared, and the results indicate that both models performed well for humid and semi-humid systems, and SVM generally perform better than ANN in the streamflow simulation of all catchments.
英文关键词	streamflow artificial neural network simulation forecasting support vector machine evolutionary strategy
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	Green Submitted, gold
收录类别	SCI-E
WOS记录号	WOS:000459735100084
WOS关键词	RIVER FLOW ; GENETIC ALGORITHM ; INFERENCE SYSTEM ; FLASH FLOODS ; MODEL ; RUNOFF ; PREDICTION ; REGRESSION ; SIMULATION ; SELECTION
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
来源机构	河海大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/219164
作者单位	Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Bafitlhile, Thabo Michael,Li, Zhijia. Applicability of epsilon-Support Vector Machine and Artificial Neural Network for Flood Forecasting in Humid, Semi-Humid and Semi-Arid Basins in China[J]. 河海大学,2019,11(1).
APA	Bafitlhile, Thabo Michael,&Li, Zhijia.(2019).Applicability of epsilon-Support Vector Machine and Artificial Neural Network for Flood Forecasting in Humid, Semi-Humid and Semi-Arid Basins in China.WATER,11(1).
MLA	Bafitlhile, Thabo Michael,et al."Applicability of epsilon-Support Vector Machine and Artificial Neural Network for Flood Forecasting in Humid, Semi-Humid and Semi-Arid Basins in China".WATER 11.1(2019).