Procedures for Using Expert Judgment in Risk Analysis
Procedures for Using Expert Judgment in Risk Analysis
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DOI：
10.1007/978-94-011-2438-6_12
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发表时间：
1992
影响因子：
5.2
通讯作者：
R. Cooke
中科院分区：
文献类型：
--
作者：
R. Cooke
本章描述了为概率风险分析开发专家判断数据的分步程序。文献中可以找到许多结合专家判断的模型（有关调查，请参阅 Cooke，1991）。然而，根据向荷兰住房、物质规划和环境部以及欧洲航天局的建议，目前仅建议实施所谓的经典模型。专家判断数据的开发分为九个阶段，在本章的相应部分中进行了阐述：1.问题识别阶段2.专家识别阶段3.专家选择阶段4.问题制定阶段5.校准变量选择阶段6.启发阶段7.组合阶段8.差异分析/反馈阶段9.文档阶段从广义上讲，概率风险评估可以分为两个部分。其中一部分可以称为事故预测，涉及对不良事件（有时称为热门事件）发生率的评估。这一阶段的主要方法是故障树分析，输入数据通常涉及基本事件的发生率。除了故障树本身之外，这部分的物理建模通常仅限于确定组件的寿命分布。
This chapter describes step by step procedures for the development of expert judgment data for probabilistic risk analysis. Many models for combining expert judgments can be found in the literature (for a survey see Cooke, 1991). However, consistent with recommendations to the Dutch Ministery of Housing, Physical Planning and Environment, and to the European Space Agency, only the so called Classical Model is recommended for implementation at this time. The development of expert judgment data is broken into nine phases, which are addressed in the corresponding sections of this chapter:1.The problem identification phase2.The expert identification phase3.The expert choice phase4.The question formulation phase5.The calibration variable selection phase6.The elicitation phase7.The combination phase8.The discrepancy analysis / feedback phase9.The documentation phaseBroadly speaking, a probabilistic risk assessment can be broken into two parts. One part, which may be denotedaccident prediction,concerns the assessment of the occurrence rates of undesired events (sometimes called Top Events). The dominant methodology in this phase is fault tree analysis, and the input data typically concerns occurrence rates of basic events. Beyond the fault tree itself, the physical modelling in this part is generally confined to the determination of life distributions for components.