Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jlp.2012.08.001
Title: Accident analysis model based on Bayesian Network and Evidential Reasoning approach
Authors: Wang, Y.F.
Xie, M. 
Chin, K.-S.
Fu, X.J.
Keywords: Accident analysis model
Bayesian Network (BN)
Evidential Reasoning (ER) approach
Human Factors Analysis and Classification System (HFACS)
Issue Date: Jan-2013
Source: Wang, Y.F., Xie, M., Chin, K.-S., Fu, X.J. (2013-01). Accident analysis model based on Bayesian Network and Evidential Reasoning approach. Journal of Loss Prevention in the Process Industries 26 (1) : 10-21. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jlp.2012.08.001
Abstract: In this paper, an accident analysis model is proposed to develop the cost-efficient safety measures for preventing accidents. The model comprises two parts. In the first part, a quantitative accident analysis model is built by integrating Human Factors Analysis and Classification System (HFACS) with Bayesian Network (BN), which can be utilized to present the corresponding prevention measures. In the second part, the proposed prevention measures are ranked in a cost-effectiveness manner through Best-Fit method and Evidential Reasoning (ER) approach. A case study of vessel collision is analyzed as an illustration. The case study shows that the proposed model can be used to seek out accident causes and rank the derived safety measures from a cost-effectiveness perspective. The proposed model can provide accident investigators with a tool to generate cost-efficient safety intervention strategies. © 2012 Elsevier Ltd.
Source Title: Journal of Loss Prevention in the Process Industries
URI: http://scholarbank.nus.edu.sg/handle/10635/62991
ISSN: 09504230
DOI: 10.1016/j.jlp.2012.08.001
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