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Journal Article

Citation

Chen J, Zhang M, Yu S, Wang J. Procedia Eng. 2018; 211: 63-69.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.proeng.2017.12.138

PMID

unavailable

Abstract

To improve the efficiency of emergency rescue in transportation accidents of hazardous materials(HAZMAT), a Bayesian network(BN) was developed in this paper to estimate the accident handling time. Also, based on this BN, the difficulty of handling every types of accidents can be quantified. According to theoretical analysis and literature review, 7 nodes (season, time, type of road, type of HAZMAT, the former accident, the secondary accident and handling time) are used to set up the BN. The value of mutual information was calculated to refine the BN. A database of 902 transportation accident of HAZMAT cases was built up for Bayesian parameter learning. Based on the parameter learning of BN, the results were summarized as follow: (1) The BN could be used to estimate the probabilities of handling time in different periods which include '0 to 2 hours', '2 to 4 hours', '4 hours and more'. (2) The difficulty of each type of accident can be ordered as follow: rollover> rear-end> internal fault≈ impact> falling> tire fault> vehicle body fire. Leakage>combustion explosion.


Language: en

Keywords

accident handling time; Bayesian network; emergency rescue; hazardous materials transportation accidents

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