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Chaotic prediction for short-term traffic ?ow of optimized B

发布时间:2016-05-26 17:28

  本文关键词:遗传算法优化BP神经网络的短时交通流混沌预测,由笔耕文化传播整理发布。


遗传算法优化BP神经网络的短时交通流混沌预测 Chaotic prediction for short-term traffic ?ow of optimized BP neural network based on genetic algorithm

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摘要:

为了提高BP神经网络预测模型对混沌时间序列的预测准确性,提出了一种基于遗传算法优化BP神经网络的改进混沌时间序列预测方法.利用遗传算法优化BP神经网络的权值和阈值,然后训练BP神经网络预测模型以求得最优解,并将该预测方法应用到几个典型混沌时间序列和实测短时交通流时间序列进行有效性验证.仿真结果表明,该方法对典型混沌时间序列和短时交通流具有较好的非线性拟合能力和更高的预测准确性.

Abstract:

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.


  本文关键词:遗传算法优化BP神经网络的短时交通流混沌预测,由笔耕文化传播整理发布。



本文编号:50219

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