基于神经网络的淮河流域年径流量预测模型  

Prediction Model of Annual Runoff in Huaihe River Basin Based on the Neural Network

作　　者：柴燕丽 孟令建[2] 

机构地区：[1]安徽省蚌埠水文水资源局,安徽蚌埠233000 [2]安徽省蚌埠市第九中学,安徽蚌埠233000

出　　处：《水资源与水工程学报》2009年第1期58-61,共4页Journal of Water Resources and Water Engineering

基　　金：国家自然科学基金(10176010)

摘　　要：利用M atlab神经网络工具箱,以淮河流域中游蚌埠(吴家渡)站的水文数据为基础,以流域代表站降水量作为基本影响因子,建立了淮河水域蚌埠段年径流量的E lm an神经网络预测模型。人工神经网络方法被引入水文预报工作中。结果表明,人工神经网络技术可应用于流域年径流量的预报研究,且E lm an神经网络的模型其强大的非线性和容错能力,显示出比相关分析、时间序列分析更有效,运算速度快,合理、可靠,具有较好的适应性和预报精度,可为水资源规划和配置提供依据。对开展水资源调查评价、综合规划等水文水资源领域的研究有着重要的意义。Based on the observed hydrologic data obtained from Bengbu Station in the middle of Huaihe River, Using the Matlab neural network toolbox and the rainfall as the basic factor, the Elman neural network prediction model is established. The results indicated that artificial neural network technology can be applied to forecasting the annual runoff in the basin. The Elman neural network predication model is generally reasonable, reliable and has better adaptability and forecasting accuracy with intensive non-liner and contain fault capacity.

关 键 词：ELMAN神经网络 降水量 年径流量 淮河流域 

分 类 号：P338[天文地球—水文科学] TP183[水利工程—水文学及水资源]