In railway system, track inspection vehicles regularly measure the vertical and lateral irregularities of each rail in order to ensure the safe running of railway. Derailment coefficient is an important indicator of the vehicle safety when the vertical wheel-rail force and lateral wheel-rail force are integrated together. In this paper, NARX neural network is proposed to predict derailment coefficient by measuring the track irregularities. In order to improve the generalization of the neural networks, the Bayesian Regularization algorithm is employed to train the neural networks. The experiments are carried out and the results show that the NARX neural network with Bayesian Regularization algorithm can predict derailment coefficient accurately.


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    Title :

    The Prediction of Derailment Coefficient Using NARX Neural Network


    Contributors:
    Pang, Xue-Miao (author) / Qin, Yong (author) / Xing, Zong-Yi (author) / Jia, Li-Min (author)

    Conference:

    First International Conference on Transportation Information and Safety (ICTIS) ; 2011 ; Wuhan, China


    Published in:

    ICTIS 2011 ; 2235-2244


    Publication date :

    2011-06-16




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English






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