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Credibility Assessment of Simulation Models Using Hesitant Cloud Linguistic Term Sets

机译:使用犹豫云语言术语集的仿真模型的可信度评估

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Credibility assessment of a simulation model is a hard problem as subjectivity is always involved. Linguistic expressions are much more straightforward and friendlier for a subject matter expert (SME) to represent qualitative judgments. Therefore, an assessment method based on hesitant cloud linguistic term sets (HCLTSs) is proposed in this paper. SMEs use context-free grammars and linguistic expressions to express their opinions. Then, these linguistic expressions are transformed into HCLTSs. Finally, aggregation results are calculated by synthetic cloud algorithm and weighted average cloud algorithm. An example under multiple-criteria group decision making is presented to illustrate the proposed method for credibility assessment.
机译:由于始终涉及主观性,仿真模型的可信度评估是一个难题。语言表达更加简单,对于一个主题专家(中小企业)来说更友好,以代表定性判断。因此,本文提出了一种基于犹豫不决语言术语集(HCLTS)的评估方法。中小企业使用免费的语法和语言表达来表达他们的意见。然后,这些语言表达式转变为HCLTS。最后,通过合成云算法和加权平均云算法计算聚合结果。提出了在多标准组决策下的一个例子来说明拟议的可信度评估方法。

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