• DocumentCode
    2246445
  • Title

    Traffic volume prediction based on improved Grey self-adaptable prediction formula

  • Author

    Xu, Na ; Zhang, Xin-rui

  • Author_Institution
    Coll. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
  • Volume
    2
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    1027
  • Lastpage
    1030
  • Abstract
    Traffic volume prediction is the key approach of highway planning stage. Grey forecast model can be used to predict the traffic volume under the condition of lacking traffic volume datum. This paper firstly points out the defect of Grey prediction formula in traditional GM(1,1) model through analyzing the Grey forecast theory, then modifies and expands the old formula, propose the new prediction formula, which gives a new way to improve the prediction accuracy. Next, constitutes the Grey self-adaptable model based on the new prediction formula for prolonging the prediction period. Finally, employs the model in traffic volume prediction for a certain station in Hebei Province. The result obtains that the simulation effect and the prediction accuracy using the new formula is higher than the result of the traditional GM(1,1) model. The case study indicates that the prediction method is not only reasonable in theory but also owns good application value in traffic volume prediction.
  • Keywords
    forecasting theory; grey systems; prediction theory; road traffic; transportation; Grey forecast model; Grey self adaptable prediction formula; Hebei province; highway planning; traffic volume prediction; Accuracy; Adaptation model; Biological system modeling; Data models; Mathematical model; Predictive models; Solid modeling; GM(1, 1); Grey prediction; MGM(1, 1); Traffic volume;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5580624
  • Filename
    5580624