Open AccessAnalysis of Subway Fire Accident Based on Bayesian Network
Author(s) -
Ying Li,
Wenyu Rong
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1910/1/012039
Subject(s) - train , event (particle physics) , bayesian network , transport engineering , fire safety , computer science , engineering , civil engineering , geography , artificial intelligence , cartography , physics , quantum mechanics
Subway stations and trains are densely populated public places. Once fire breaks out, it will cause casualties and seriously threaten people’s life and property safety. In order to explore the deep causes of subway fire and prevent subway fire accidents, this paper makes statistics on the causes of subway fire in various countries in recent years and classifies them. On this basis, the Bayesian network for subway fire causes is constructed, the probability of subway fire occurrence and the posterior probability of each basic event are calculated by using the prior probability of each basic event, and the corresponding safety management measures are proposed. The results show that the method can find out the probability of each basic event in subway fire by quantitative calculation, and the method is scientific and effective, which can provide reference for subway safety management.