In prediction of railway passenger traffic volume based on support vector regression, different input points make different contribution to the predictive function. A new prediction method for railway passenger volume, named weighted LS-SVM, is presented in this paper, different weighting factors are assigned to each input points by the linear interpolation function. The railway passenger volume from 1985 to 2002 are used and the results show that the weighted LS-SVM outperforms the standard LS-SVM.


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    Title :

    Prediction of Railway Passenger Traffic Volume Based on Weighted LS-SVM


    Contributors:
    Han, Hu (author) / Dang, Jian-Wu (author) / Ren, En-En (author)


    Publication date :

    2008-10-01


    Size :

    336629 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English







    Railway Passenger Station Daily Traffic Working Plan Automation

    Chen, T. / Lu, H.-x. / China Communications and Transportation Association; Transportation & Development Institute (American Society of Civil Engineers) | British Library Conference Proceedings | 2007