• DocumentCode
    632637
  • Title

    A Bayesian network model for evacuation time analysis during a ship fire

  • Author

    Sarshar, Parvaneh ; Radianti, Jaziar ; Granmo, Ole-Christoffer ; Gonzalez, Jose J.

  • Author_Institution
    Dept. of ICT, Univ. of Agder, Grimstad, Norway
  • fYear
    2013
  • fDate
    16-19 April 2013
  • Firstpage
    100
  • Lastpage
    107
  • Abstract
    We present an evacuation model for ships while a fire happens onboard. The model is designed by utilizing Bayesian networks (BN) and then simulated in GeNIe software. In our proposed model, the most important factors that have significant influence on a rescue process and evacuation time are identified and analyzed. By applying the probability distribution of the considered factors collected from the literature including IMO, real empirical data and practical experiences, the trend of the rescue process and evacuation time can be evaluated and predicted using the proposed model. The results of this paper help understanding about possible consequences of influential factors on the security of the ship and help to avoid exceeding evacuation time during a ship fire.
  • Keywords
    Bayes methods; emergency management; fires; ships; statistical distributions; Bayesian network model; GeNIe software; IMO; evacuation time analysis; probability distribution; rescue process; ship fire; ship security; Analytical models; Computational modeling; Educational institutions; Fires; Marine vehicles; Standards; Bayesian network (BN); evacuation time; rescue process; ship fire;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Dynamic and Uncertain Environments (CIDUE), 2013 IEEE Symposium on
  • Conference_Location
    Singapore
  • Type

    conf

  • DOI
    10.1109/CIDUE.2013.6595778
  • Filename
    6595778