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《Northwest Water Power》 2003-04
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Daily runoff prediction based on integration of genetic and back-propagation algorithms

GONG Chuan-li, KANG Ling, JIANG Tie-bing(College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan430074,China)  
A new method for training Artificial Neural Network(ANN) based daily runoff prediction model is presented. In this method, the genetic algorithm(GA), a general-purpose global search algorithm is used to train the neural network prediction model by updating the weights to minimize the error between the network output and the desired output. It overcomes the limitations of the back-propagation algorithm in slow convergent rate and getting into local optima. The example demonstrates that this method improves the prediction precision.
【Fund】: 武汉市晨光计划项目(20005004028)资助.
【CateGory Index】: TV124
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