• DocumentCode
    3470743
  • Title

    Research on the Prediction of Urban Passenger Transport based on Support Vector Machine

  • Author

    Zhang, Wenfeng ; Shi, Zhongke ; Liu, Qin

  • Author_Institution
    Northwestern Polytech. Univ., Xi´´an
  • fYear
    2007
  • fDate
    18-21 Aug. 2007
  • Firstpage
    862
  • Lastpage
    865
  • Abstract
    The prediction model of urban passenger transport is proposed in this paper, which can provide the theoretical foundation for the government management to make decision and to predict passenger volume of urban transport accurately. The prediction model of urban passenger transport is established by using support vector machine (SVM), combining with the volume of the urban of passenger transport in Xi´an over years. The prediction model of urban passenger transport is validated, and the simulation results indicate that this prediction model is effective. Besides it has stronger fitting than the prediction based on BP neural network.
  • Keywords
    government data processing; prediction theory; support vector machines; traffic engineering computing; transportation; government management; support vector machine; urban passenger transport prediction; Automation; Cities and towns; Educational institutions; Logistics; Predictive models; Road transportation; Support vector machine classification; Support vector machines; Telecommunication traffic; Traffic control; Support vector machine; prediction model; urban passenger transport;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2007 IEEE International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-1531-1
  • Type

    conf

  • DOI
    10.1109/ICAL.2007.4338685
  • Filename
    4338685