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《China Rural Water and Hydropower》 2010-11
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Nonlinear Mix Regression Model for Annual Flow Forecasting

WU Xia-ning1,JIANG Yan2(1.Sinohydro Corporation Limited,Beijing 100044,China;2.State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-environmental Science,Chinese Academy of Science,Beijing 100085,China)  
There are many methods for medium-and long-term runoff forecasting,such as time series,multiple linear regression and so on,which often have deviation in forecasting precision.This paper is an attempt to establish a nonlinear mix regression model(NMR) for annual runoff forecasting,in which year flow is an auto-regression factor,precipitation and air temperature is regression factor.And BP neural network is used to solve NMR.Compared with the auto-regression model,the linear multi-regression model and linear mix regression model,NMR can remarkably improve forecasting precision.The results show that NMR can well simulate annual flow.
【Fund】: 国家自然科学基金资助项目(50809004)
【CateGory Index】: P333.6
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