• DocumentCode
    3598623
  • Title

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

  • Author

    Han, Hu ; Dang, Jian-wu ; Ren, En-En

  • Author_Institution
    Sch. of Math., Phys. & Software Eng., Lanzhou Jiaotong Univ., Lanzhou
  • Volume
    1
  • fYear
    2008
  • Firstpage
    227
  • Lastpage
    230
  • Abstract
    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.
  • Keywords
    forecasting theory; interpolation; least squares approximations; railways; support vector machines; least squares approximations; linear interpolation function; railway passenger traffic volume prediction; support vector regression; Automation; Interpolation; Least squares methods; Mathematics; Physics computing; Prediction methods; Rail transportation; Software engineering; Support vector machines; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
  • Print_ISBN
    978-0-7695-3357-5
  • Type

    conf

  • DOI
    10.1109/ICICTA.2008.17
  • Filename
    4659478