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A novel linguistic representative model based on discrete fuzzy numbers for multi-granularity linguistic decision-making

机译:基于离散模糊数的新型语言表示模型用于多粒度语言决策

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Many decision-making problems use vague and imprecise information in linguistic variable formats as preferences. In this paper, we present a linguistic representative model based on discrete fuzzy numbers whose support is a subset of consecutive natural numbers. The arbitrary linguistic term is defined to give decision makers more freedom to express their preferences. The discrete fuzzy weighted normal operators defined on a finite chain in accordance with the granularity of linguistic term set are used to complete the aggregation process.
机译:许多决策问题使用语言可变格式的模糊和不精确信息作为首选项。在本文中,我们提出了一种基于离散模糊数的语言表示模型,该离散数的支持是连续自然数的子集。任意语言术语被定义为使决策者有更多的自由来表达自己的偏好。根据语言术语集的粒度,在有限链上定义的离散模糊加权正态算符用于完成聚合过程。

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