用于可靠性和风险评估的定性-定量贝叶斯信念网络

Chengdong Wang, A. Mosleh
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引用次数: 8

摘要

本文提出了贝叶斯信念网络(BBN)的扩展,使定性和定量似然尺度在推理中都能使用。该方法被命名为QQBBN(定性-定量贝叶斯信念网络)。当缺乏估计概率的定量数据和专家不愿以定量方式表达他们的意见时,包括定性尺度尤其有用。在可靠性和风险分析中,当系统的人为和组织根源被明确建模时,就会出现这种情况。由于技术水平的限制和缺乏适当的定量指标,这些原因往往无法量化。本文描述了所提出的QQBBN框架,并通过一个简单的例子说明了它的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Qualitative-Quantitative Bayesian Belief Networks for reliability and risk assessment
This paper presents an extension of Bayesian belief networks (BBN) enabling use of both qualitative and quantitative likelihood scales in inference. The proposed method is accordingly named QQBBN (Qualitative-Quantitative Bayesian Belief Networks). The inclusion of qualitative scales is especially useful when quantitative data for estimation of probabilities are lacking and experts are reluctant to express their opinions quantitatively. In reliability and risk analysis such situation occurs when for example human and organizational root causes of systems are modeled explicitly. Such causes are often not quantifiable due to limitations in the state of the art and lack of proper quantitative metrics. This paper describes the proposed QQBBN framework and demonstrates its uses through a simple example.
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