吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (03): 646-653.doi: 10.7964/jdxbgxb201303015

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Multi-step traffic flow prediction model based on wavelet and echo state network

YANG Fei1,2,3, FANG Bin-xing1,2, WANG Chun-lu1,2, ZUO Xing-quan1,2, LI Li-xiang1,2, PING Yuan1,2   

  1. 1. School of Computer Science, Beijing University of Post and Telecommunications, Beijing 100876, China;
    2. Key Laboratory of Trustworthy Distributed Computing and Service of the Ministry of Education of China, Beijing University of Post and Telecommunications, Beijing 100876, China;
    3. Nanjing Panda Electronics Company Limited, Nanjing 210002, China
  • Received:2012-01-17 Online:2013-05-01 Published:2013-05-01

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Abstract: In light of the noisy chaotic characteristics of traffic flow, a new multi-step traffic flow prediction model based on wavelet and echo state network was proposed. Utilizing multi-scale decomposition method of wavelet, the proposed model restricts the interference of noisy components to the dynamic behavior of the traffic flow; meanwhile it extracts the chaotic low-frequency component, which possesses most of the energy of traffic flow. In predicting the multi components concurrently, the strong prediction capacity of echo state network for chaotic low-frequency component was utilized effectively to ensure the accuracy of multi-step traffic flow prediction. The results of prediction of the real traffic flow in Xizhimen Bridge of Beijing show that the prediction accuracy is significantly improved by the proposed multi-step model in comparison with the traditional echo state network model. Under the condition of high prediction accuracy, the maximum predictable step is also increased by the proposed model.

Key words: engineering of communications and transportation system, traffic flow prediction, echo state network, chaotic attractor, phase space reconstruction

CLC Number: 

  • U491
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