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宜昌站洪峰流量过程神经网络预测模型研究
引用本文:袁晶,张为,张小峰.宜昌站洪峰流量过程神经网络预测模型研究[J].科学技术与工程,2007,7(23):6096-6099.
作者姓名:袁晶  张为  张小峰
作者单位:1. 长江水利委员会水文局,武汉,430010
2. 武汉大学水资源与水电工程科学国家重点实验室,武汉,430072
基金项目:国家重大基础研究计划(973)项目(2003CB415200)资助
摘    要:以长江上游寸滩-宜昌河段为研究对象,建立了考虑区间降雨的河道洪水预报BP神经网络模型,论证了应用人工神经网络模型进行洪水预报的可行性。以1982年至1986年的洪水预报作为仿真,表明该模型能较好地反映区间降雨的影响,对大中小各种洪水过程都能进行准确预报。

关 键 词:洪水预报模型  洪峰流量  区间降雨  人工神经网络  预见期
文章编号:1671-1819(2007)23-6096-04
修稿时间:2007-06-25

Flood Peak Discharge Forecasting Model of Yichang Using Artificial Neutral Network
YUAN Jing,ZHANG Wei,ZHANG Xiao-feng.Flood Peak Discharge Forecasting Model of Yichang Using Artificial Neutral Network[J].Science Technology and Engineering,2007,7(23):6096-6099.
Authors:YUAN Jing  ZHANG Wei  ZHANG Xiao-feng
Institution:Hydrology Bureau, Yangtze River Water Resource Commission, Wuhan 430010, P. R. China; State Key Laboratory of Water Resources and Hydropower Engineering Science , Wuhan University Wuhan 430072, P. R, China 430072
Abstract:With BP artificial neural network, a model is developed to forecast flood propagation in Cuntan-Yichang reach of Yangtze River. In the model, local inflow from the rainfall in the catchment between Cuntan-Yichang was considered. Comparison between computed result and measured data from 1982 to 1986 show that the model can simulate the flood process at Yichang correctly, especially, to some representative discharge, which proved the feasibility of this model.
Keywords:flood forecasting model flood peak discharge local rainfall artificial neural network Foresight time
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