• DocumentCode
    519749
  • Title

    The short-term traffic flow prediction based on neural network

  • Author

    Hu, Wusheng ; Liu, Yuanlin ; Li, Li ; Xin, Shujie

  • Author_Institution
    Transp. Coll., Southeast Univ., Nanjing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    21-24 May 2010
  • Abstract
    As we all know, to predict the short-term traffic flow accurately and efficiently is the premise and key of traffic management and control. Based on these existing study, this paper selected BP neural network model in which the traffic flow difference was taken as the input parameter, applied the thought of dynamic rolling prediction to design a new short-term traffic flow prediction method, and wrote the corresponding program. Then using the actual observation data of traffic flow presented the model structure, thought and calculation steps of this new method. The results show this method is feasibility, reliability, and of some practical value.
  • Keywords
    backpropagation; neural nets; traffic engineering computing; BP neural network; short-term traffic flow prediction; traffic control; traffic management; Artificial neural networks; Communication system traffic control; Electronic mail; Neural networks; Prediction methods; Predictive models; Telecommunication traffic; Traffic control; Transportation; Vehicle dynamics; BP Algorithm; Dynamic Rolling Prediction; Neural Network; Short-term Traffic Flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future Computer and Communication (ICFCC), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5821-9
  • Type

    conf

  • DOI
    10.1109/ICFCC.2010.5497785
  • Filename
    5497785