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《Control and Decision》 2011-10
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Chaotic prediction for short-term traffic ?ow of optimized BP neural network based on genetic algorithm

LI Song1,LIU Li-jun2,XIE Yong-le1(1.School of Management,Hebei University,Baoding 071002,China;2.School of Business Administration,Hebei University of Economics and Business,Shijiazhuang 050061,China)  
In order to improve the prediction accuracy of BP neural network model for chaotic time series,a prediction method for chaotic time series of optimized BP neural network based on genetic algorithm(GA) is presented.The GA is used to optimize the weights and thresholds of BP neural network,and the BP neural network is trained to search for the optimal solution.The efficiency of the proposed prediction method is tested by the simulation of several typical nonlinear systems and time series of real traffic ?ow.The simulation results show that the proposed method has better fitting ability and higher accuracy.
【Fund】: 国家自然科学基金项目(50478088);; 河北省高等学校人文社会科学研究重点项目(SKZD2011106)
【CateGory Index】: U491.112
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