Literature DB >> 28068456

An Evidential Reasoning-Based CREAM to Human Reliability Analysis in Maritime Accident Process.

Bing Wu1,2, Xinping Yan1,3, Yang Wang1,3, C Guedes Soares2.   

Abstract

This article proposes a modified cognitive reliability and error analysis method (CREAM) for estimating the human error probability in the maritime accident process on the basis of an evidential reasoning approach. This modified CREAM is developed to precisely quantify the linguistic variables of the common performance conditions and to overcome the problem of ignoring the uncertainty caused by incomplete information in the existing CREAM models. Moreover, this article views maritime accident development from the sequential perspective, where a scenario- and barrier-based framework is proposed to describe the maritime accident process. This evidential reasoning-based CREAM approach together with the proposed accident development framework are applied to human reliability analysis of a ship capsizing accident. It will facilitate subjective human reliability analysis in different engineering systems where uncertainty exists in practice.
© 2017 Society for Risk Analysis.

Entities:  

Keywords:  CREAM; evidential reasoning; human reliability analysis; maritime accident process; safety engineering

Year:  2017        PMID: 28068456     DOI: 10.1111/risa.12757

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  3 in total

1.  Dynamic Human Error Assessment in Emergency Using Fuzzy Bayesian CREAM.

Authors:  Marzieh Abbasinia; Omid Kalatpour; Majid Motamedzadeh; Alireza Soltanian; Iraj Mohammadfam
Journal:  J Res Health Sci       Date:  2020-02-16

2.  Identifying Cognitive Mechanism Underlying Situation Awareness of Pilots' Unsafe Behaviors Using Quantitative Modeling.

Authors:  Shaoqi Jiang; Weijiong Chen; Yutao Kang; Jiahao Liu; Wanglai Kuang
Journal:  Int J Environ Res Public Health       Date:  2021-03-16       Impact factor: 3.390

3.  Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.

Authors:  Yaju Wu; Kaili Xu; Ruojun Wang; Xiaohu Xu
Journal:  PLoS One       Date:  2021-08-02       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.