Accident analysis model based on Bayesian Network and Evidential Reasoning approach

被引：59

作者：

Wang, Yan Fu ^{[1
]}

Xie, Min ^{[2
,3
]}

Chin, Kwai-Sang ^{[3
]}

Fu, Xiu Ju ^{[4
]}

机构：

[1] China Univ Petr, Dept Safety Engn, Qingdao 266555, Peoples R China

[2] Natl Univ Singapore, Dept Ind & Syst Engn, Singapore 119260, Singapore

[3] City Univ Hong Kong, Dept Syst Engn & Engn Management, Kowloon Tong, Hong Kong, Peoples R China

[4] Inst High Performance Comp, Singapore 138632, Singapore

来源：

JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES | 2013年 / 26卷 / 01期

关键词：

Accident analysis model; Human Factors Analysis and Classification; System (HFACS); Bayesian Network (BN); Evidential Reasoning (ER) approach; FORMAL SAFETY ASSESSMENT; DECISION-ANALYSIS; UNCERTAINTY;

D O I：

10.1016/j.jlp.2012.08.001

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

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. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：10 / 21

页数：12

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