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Epistemic Uncertainty Analysis: An Approach Using Expert Judgment and Evidential Credibility

机译:认知不确定性分析:一种使用专家判断和证据可信度的方法

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When dealing with complex systems, all decision making occurs under some level of uncertainty. This is due to the physical attributes of the system being analyzed, the environment in which the system operates, and the individuals which operate the system. Techniques for decision making that rely on traditional probability theory have been extensively pursued to incorporate these inherent aleatory uncertainties. However, complex problems also typically include epistemic uncertainties that result from lack of knowledge. These problems are fundamentally different and cannot be addressed in the same fashion. In these instances, decision makers typically use subject matter expert judgment to assist in the analysis of uncertainty. The difficulty with expert analysis, however, is in assessing the accuracy of the expert's input. The credibility of different information can vary widely depending on the expert’s familiarity with the subject matter and their intentional (i.e., a preference for one alternative over another) and unintentional biases (heuristics, anchoring, etc.). This paper proposes the metric of evidential credibility to deal with this issue. The proposed approach is ultimately demonstrated on an example problem concerned with the estimation of aircraft maintenance times for the Turkish Air Force.
机译:当处理复杂的系统时,所有决策都在一定程度的不确定性下进行。这是由于要分析的系统的物理属性,系统在其中运行的环境以及系统的个人所致。依靠传统概率论进行决策的技术已被广泛采用,以结合这些固有的不确定性不确定性。但是,复杂的问题通常还包括由于缺乏知识而导致的认知不确定性。这些问题根本不同,无法以相同的方式解决。在这些情况下,决策者通常使用主题专家的判断来协助不确定性分析。但是,专家分析的困难在于评估专家输入的准确性。不同信息的可信度可能会有所不同,这取决于专家对主题的熟悉程度以及其故意(即,相对于另一种选择是一种偏爱)和无意间的偏见(启发式,锚定等)。本文提出了证据可信度的度量标准来解决这个问题。最终,在与土耳其空军的飞机维修时间估算有关的示例问题上证明了该方法。

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