Classification-based flood forecasting model using artificial neural networks

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	Classification-based flood forecasting model using artificial neural networks
	Xia Jun
	2007
关键词	Artificial intelligence Computer simulation Forecasting Neural networks Rain Runoff Self organizing maps
英文摘要	Fuzzy C Means (FCM) clustering method and Self-Organizing Feature Map (SOM) clustering method were both employed to decomposed the flow hydrograph to several segments, and the situation of rain and runoff was analyzed in each segment, then two hybrid artificial neural networks (FCMMFN and SOMMFN), based on Fuzzy C Means clustering method and Self-Organizing Feature Map clustering method separately, were applied to simulate the rainfall-runoff relationship. The case study in Wangjiachang Reservoir indicated that two clustering methods have the ability to decomposed the flow hydrograph to several segments in which the under-lying mechanisms of stre-amflow generation appear different. Besides, the two classification-based artificial neural networks are both superior to the single multi-layer feedforward network, furthermore, the performance of FCMMFN is better than the one of SOMMFN.
出处	Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition)
卷	39 期:3 页:34-40
收录类别	EI
语种	英语
内容类型	EI期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/24421]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Xia Jun. Classification-based flood forecasting model using artificial neural networks. 2007.