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A Quantitative Study of the Occurrence of a Railway Accident Based on Belief Functions

  • Felipe Aguirre
  • Mohamed Sallak
  • Walter Schön
  • Fabien Belmonte
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 164)

Abstract

In the field of railway systems, there is a great interest to include the human factor in the risk analysis process. Indeed, a great number of accidents are consider to be triggered by the human factors interacting in the situation. Several attempts have been made to include human factors in safety analysis, but they generally attack the problem in a qualitative way. The choice of qualitative methods arises from the difficulty to elicit human behavior and the effects on systems safety. This paper presents a first attempt to account for the human factor by using the generalized bayesian theory and fault tree analysis.

Keywords

Epistemic Uncertainty Basic Belief Belief Function Fault Tree Analysis Conditional Belief 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Felipe Aguirre
    • 1
  • Mohamed Sallak
    • 1
  • Walter Schön
    • 1
  • Fabien Belmonte
    • 2
  1. 1.Centre de recherche de RoyallieuUniversity of Technology of Compiègne. HEUDIASYC UMR 6599CompiègneFrance
  2. 2.Alstom TransportSaint-Ouen cedexFrance

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