• DocumentCode
    3022876
  • Title

    Traffic accidents inference based on Bayesian networks

  • Author

    Cui, Fangda ; Cheng, Xiangyang

  • Author_Institution
    Sch. of Math. & Comput. Sci., Fuyang Teachers´´ Coll., Fuyang, China
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    6151
  • Lastpage
    6155
  • Abstract
    Bayesian network is a graphics mode which is used to show joint probability distribution. It reflects the potential dependence relationship among variables. The Bayesian network has already been the powerful tool to solve various uncertain questions. This thesis collects some information about traffic accidents in a city of Anhui Province. According to the information, it gets the Markov network firstly. Secondly, it gives directions to all edges of the Markov network according to the mutual degree of dependence. Finally, it reaches the Bayesian network which shows the relationship of uncertain factors in traffic accidents.
  • Keywords
    Markov processes; accidents; belief networks; probability; road safety; traffic engineering computing; Anhui Province; Bayesian networks; Markov network; graphics mode; probability distribution; traffic accidents inference; Accidents; Bayesian methods; Educational institutions; Information theory; Markov random fields; Research and development; Bayesian network; Markov network; conditional independence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Technology (ICMT), 2011 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-61284-771-9
  • Type

    conf

  • DOI
    10.1109/ICMT.2011.6001723
  • Filename
    6001723