Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEEM.2010.5674564
Title: A new methodology to integrate human factors analysis and classification system with Bayesian Network
Authors: Wang, Y.F.
Roohi, S.F.
Hu, X.M.
Xie, M. 
Keywords: Bayesian Network
Fuzzy analytical hierarchy process
Human factors analysis and classification system
Issue Date: 2010
Source: Wang, Y.F.,Roohi, S.F.,Hu, X.M.,Xie, M. (2010). A new methodology to integrate human factors analysis and classification system with Bayesian Network. IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management : 1776-1780. ScholarBank@NUS Repository. https://doi.org/10.1109/IEEM.2010.5674564
Abstract: In this paper, a new methodology, which integrates human factors analysis and classification system (HFACS) with Bayesian Network (BN), is proposed to assess the contribution of human and organizational factors in maritime accidents. As a means of making up the lack of quantitative analysis within HFACS, the integration of BN and fuzzy analytical hierarchy process (AHP) have been selected to estimate quantitatively the contribution of human error to the accident. At the same time, the HFACS' 4-level structure provides a systematic guideline in the construction of the BN to model how human errors are related to form a network. Fuzzy AHP and decomposition method are applied to estimate the conditional probabilities of BN, which is more efficient manner and can reduce subjective biases. A case study of ship collision showed that the method is more flexible to seek out the critical latent human and organizational errors using the advantages of both techniques. ©2010 IEEE.
Source Title: IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management
URI: http://scholarbank.nus.edu.sg/handle/10635/72249
ISBN: 9781424485031
DOI: 10.1109/IEEM.2010.5674564
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