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首页> 外文会议>2011 IEEE International Conference on Intelligence and Security Informatics >Quantitative risk analysis model of integrating fuzzy fault tree with Bayesian Network
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Quantitative risk analysis model of integrating fuzzy fault tree with Bayesian Network

机译：模糊故障树与贝叶斯网络融合的定量风险分析模型

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摘要

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.
机译：本文提出了一种与贝叶斯网络（BN）集成模糊断层树（FFT）的新量化风险分析模型。第一步涉及描述基于Takagi和Sugeno模型的模糊故障树分析技术。第二步提出了将FFT转换为BN的翻译规则。基于此，通过海上火灾案例研究证明了集成算法。该示例清楚地表明，FFT可以直接转换为BN，并且可以通过BN的基本推理技术获得FFT的经典参数。通过使用这两种技术的优点，将FFT与BN集成的模型比传统的故障树模型更加灵活和有用。这种新模型不仅可以用于描述事故升级的因果效果，而且用于基于历史数据和模糊逻辑计算事故发生概率。

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