Flood forecasting research based on the chaotic BP neural network model

被引：2

作者：

Zhu, Changjun ^{[1
]}

Wu, Liping ^{[1
]}

Li, Sha ^{[1
]}

机构：

[1] Hebei Univ Engn, Coll Urban Construct, Handan 056038, Peoples R China

来源：

ADVANCED MEASUREMENT AND TEST, PARTS 1 AND 2 | 2010年 / 439-440卷

关键词：

flood forecasting; phase-space reconstruction; chaos theory; BP neural network;

D O I：

10.4028/www.scientific.net/KEM.439-440.411

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In view of the problem that the predictive results of flow quantity are not ideal for the predictive models at present. Based on the chaos identification to the flood system, chaos BP neural network model are developed combined chaos theory and BP neural netwok, flood sequences are disposed by phase-space reconstruction to be as training sample. Network structure can be determined by Mat lab toolbox. The established chaos BP model is used to predict the phenomenon of peak value for Huayuankou hydrometric station in 2006. The results show that the predictive model combined chaos theory and BP neural network, has certain reference value to improve flood forecasting accuracy as a new attempt.

引用

页码：411 / 416

页数：6

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