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首页> 外文期刊>International journal of general systems >Representation of analysis results involving aleatory and epistemic uncertainty
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Representation of analysis results involving aleatory and epistemic uncertainty

机译：涉及偶然和认知不确定性的分析结果的表示

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摘要

Procedures are described tor the representation ot results in analyses that involve both aleatory uncertainty and epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behaviour of the system under study and epistemic uncertainty deriving from a lack of knowledge about the appropriate values to use for quantities that are assumed to have fixed but poorly known values in the context of a specific study. Aleatory uncertainty is usually represented with probability and leads to cumulative distribution functions (CDFs) or complementary CDFs (CCDFs) for analysis results of interest. Several mathematical structures are available for the representation of epistemic uncertainty, including interval analysis, possibility theory, evidence theory and probability theory. In the presence of epistemic uncertainty, there is not a single CDF or CCDF for a given analysis result. Rather, there is a family of CDFs and a corresponding family of CCDFs that derive from epistemic uncertainty and have an uncertainty structure that derives from the particular uncertainty structure (e.g. interval analysis, possibility theory, evidence theory or probability theory) used to represent epistemic uncertainty. Graphical formats for the representation of epistemic uncertainty in families of CDFs and CCDFs are investigated and presented for the indicated characterisations of epistemic uncertainty.
机译：描述过程的结果表示既涉及不确定性不确定性又涉及认知不确定性，其中不确定性源于所研究系统行为的固有随机性，认知不确定性源于对使用的适当值的了解不足对于在特定研究中假设具有固定但未知值的数量。通透性不确定性通常用概率表示，并导致感兴趣的分析结果的累积分布函数（CDF）或互补CDF（CCDF）。有几种数学结构可用于表示认知不确定性，包括区间分析，可能性理论，证据理论和概率论。在存在认知不确定性的情况下，对于给定的分析结果，没有单个CDF或CCDF。而是有一个CDF族和一个CCDF族，它们来自认知不确定性，并且具有一个不确定性结构，该不确定性结构是从用来表示认知不确定性的特定不确定性结构（例如区间分析，可能性理论，证据理论或概率论）中得出的。对CDF和CCDF族的认知不确定性表示形式的图形格式进行了研究，并针对认知不确定性的指示特征进行了介绍。

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