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《Journal of Sichuan University (Engineering Science Edition)》 2005-05
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The Self-adaptive NNBR-ANN Coupling Model for Annual Runoff Forecast

WAN Xing~(1,2),DIN Jing~1,YAN Bin-zhong~1,ZHANG Xiao-li~2(1.School of Hydraulic Eng., Sichuan Univ., Chengdu 610065,China;2.Chengdu Univ. of Info. Tech., Chengdu 610041,China)  
Based on genetic algorithm on optimizing the parameter of artificial neural network and nearest neighbor bootstrapping regressive model, the automatic coupling model of NNBR-ANN is obtained. The model is applied to forecast the annual runoff of QingTong Xia of Yellow River and compare with Artificial neural network and nearest neighbor bootstrapping regressive model. It shows that the model could optimize the basic parameter and break traditional method of deciding parameter. The coupling model is smart applicable and has better foresting precision.
【Fund】: 国家自然科学重点基金资助项目(40271024 50279023)
【CateGory Index】: P338;
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