Chaotic prediction for short-term traffic ?ow of optimized BP neural network based on genetic algorithm
Yongle Xie
Abstract
Yongle Xie
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.
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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.
Key concepts: Artificial neural network, Chaotic, Genetic algorithm, Series (stratigraphy), Algorithm, Computer science, Nonlinear system, Term (time)