Please use this identifier to cite or link to this item: https://doi.org/10.1109/ISI.2011.5984095
Title: Quantitative risk analysis model of integrating fuzzy fault tree with Bayesian network
Authors: Wang, Y.F.
Xie, M. 
Ng, K.M. 
Meng, Y.F.
Keywords: Bayesian Network
Fuzzy Fault Tree
Quantitative Risk Analysis Model
Issue Date: 2011
Source: Wang, Y.F.,Xie, M.,Ng, K.M.,Meng, Y.F. (2011). Quantitative risk analysis model of integrating fuzzy fault tree with Bayesian network. Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 : 267-271. ScholarBank@NUS Repository. https://doi.org/10.1109/ISI.2011.5984095
Abstract: In this paper, a new quantitative risk analysis model of integrating fuzzy fault tree (FFT) with Bayesian Network (BN) is proposed. The first step involves describing a fuzzy fault tree analysis technique based on the Takagi and Sugeno model. The second step proposes the translation rules for converting FFT into BN. Based on this, the integration algorithm is demonstrated by an offshore fire case study. The example clearly shows that FFT can be directly converted into BN and the classical parameters of FFT can be obtained by the basic inference techniques of BN. By using the advantages of both techniques, the model of integrating FFT with BN is more flexible and useful than traditional fault tree model. This new model not only can be used for describing the causal effect of accident escalation but also for computing the occurrence probability of accident based on historical data and fuzzy logic. © 2011 IEEE.
Source Title: Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
URI: http://scholarbank.nus.edu.sg/handle/10635/72385
ISBN: 9781457700828
DOI: 10.1109/ISI.2011.5984095
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