• DocumentCode
    1876109
  • Title

    Elman Neural Network Model of Traffic Flow Predicting in Mountain Expressway Tunnel

  • Author

    Song, Xin-Sheng ; Li, Hui ; Wu, Bing-Hua ; Li, Ai-Zeng

  • Author_Institution
    Dept. of Traffic Eng., Henan Univ. of Urban Constr., Pingdingshan, China
  • fYear
    2010
  • fDate
    10-12 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Aims at the complex and dynamic nature of traffic flow in mountain expressway tunnel, through the analysis of change characteristics of traffic flow, based on BP network improve the existing expressway traffic flow model, this thesis puts forward the Elman dynamic neural network model of traffic flow predicting in mountain expressway tunnel. In practice, this model has the strong operational, we adopt it to simulate and forecast the traffic flow of JingZhu expressway ShaoGuan section, reach the purpose of theory and reality unify. Through the analysis of the traffic flow characteristics this thesis could provide a viable research idea for the rational and orderly flowing of tunnel traffic flow.
  • Keywords
    backpropagation; neural nets; traffic engineering computing; BP network; Elman dynamic neural network model; JingZhu expressway ShaoGuan section; expressway traffic flow model; mountain expressway tunnel; traffic flow forecasting; Analytical models; Artificial neural networks; Equations; Roads; Training; Vehicle dynamics; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5391-7
  • Electronic_ISBN
    978-1-4244-5392-4
  • Type

    conf

  • DOI
    10.1109/CISE.2010.5677002
  • Filename
    5677002