基于神经网络的洮河枯期径流预报模型研究  

The Research of Model of Tao River Run-Off Prediction Based on Neural Network in Dry Season

作　　者：杨新华[1] 金兴文[1] 马建立[1] 陈玉松[1] 苏军希[2] 

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050 [2]黄河水利委员会上游水文水资源局,甘肃兰州730030

出　　处：《节水灌溉》2007年第8期76-78,共3页Water Saving Irrigation

摘　　要：根据洮河50年(1957～2006年)的径流量、降雨和上游径流量数据,建立了基于反馈神经网络的Elman洮河枯季径流预报模型。利用matlab7提供的神经网络工具箱进行建模训练。仿真结果表明所采用的Elman网络预报模型精度高,为人工神经网络运用到水文预测方面提供了依据。According to the records of rain and run off of Tao River and flow of Tao upriver for 50 years (1957-2006),a Elman neural network model of dry season run-off forecast is established based on The principle of feedback artificial neural network.Then the au- thor made the model and trained the model for many times by Neural Network Toolbox of matlabT.The results of the emulation show that the ANN prediction model based on Elm,an is more precise in this paper,so it provides a basis for the application of ANN in hydrological prognosis.

关 键 词：枯季径流预报 ELMAN网络 网络训练 水文预测 

分 类 号：TV121[水利工程—水文学及水资源]