• DocumentCode
    2449853
  • Title

    Researches on the novel methodology of traffic flow prediction based on similarity

  • Author

    Cui, Licheng ; Zhang, Weishi ; Zhang, Runtong ; Zhai, Huawei ; Zhang, Xiuguo ; Xie, Xiong

  • Author_Institution
    Dept. of Inf. Sci. & Technol., Dalian Maritime Univ., Dalian, China
  • fYear
    2011
  • fDate
    14-16 Oct. 2011
  • Firstpage
    296
  • Lastpage
    300
  • Abstract
    Similarity is one of the important characteristics of traffic flow time series, it reflects the same property of every two time series, and it is very significant to traffic flow prediction and traffic guidance. There are many prediction models based on similarity, but they neglect the direct impacts of historical data more or less. So, based on similarity and referring the idea of battery discharge effects, a new prediction model is proposed, it fully takes into account the impacts of historical data on current traffic flow, its description and characteristic analysis are given in detail. Finally, its performances is analyzed and compared with other models.
  • Keywords
    time series; traffic engineering computing; historical data; similarity; time series; traffic flow prediction; Benchmark testing; Data models; Discharges; Mathematical model; Measurement; Predictive models; Time series analysis; discharge effects; prediction model; similarity; traffic flow; traffic guidance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Pattern Recognition (SoCPaR), 2011 International Conference of
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4577-1195-4
  • Type

    conf

  • DOI
    10.1109/SoCPaR.2011.6089259
  • Filename
    6089259