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首页> 外文期刊>Advances in fuzzy systems >Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making
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Distance Based Entropy Measure of Interval-Valued Intuitionistic Fuzzy Sets and Its Application in Multicriteria Decision Making

机译:区间直觉模糊集的基于距离的熵测度及其在多准则决策中的应用

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Fuzzy entropy means the measurement of fuzziness in a fuzzy set and therefore plays a vital role in solving the fuzzy multicriteria decision making (MCDM) and multicriteria group decision making (MCGDM) problems. In this study, the notion of the measure of distance based entropy for uncertain information in the context of interval-valued intuitionistic fuzzy set (IVIFS) is introduced. The arithmetic and geometric average operators are firstly used to aggregate the interval-valued intuitionistic fuzzy information provided by the decision makers (DMs) or experts corresponding to each alternative, and then the fuzzy entropy of each alternative is calculated based on proposed distance measure. Several numerical examples are solved to demonstrate the application to MCDM and MCGDM problems to show the effectiveness of the proposed approach.
机译:模糊熵意味着对模糊集中的模糊性的度量,因此在解决模糊多准则决策(MCDM)和多准则群决策(MCGDM)问题中起着至关重要的作用。在这项研究中,介绍了在区间值直觉模糊集(IVIFS)的上下文中对不确定信息基于距离的熵的度量的概念。首先利用算术和几何平均算子对决策者或专家提供的区间值直觉模糊信息进行汇总,然后根据拟议的距离测度计算出每个方案的模糊熵。求解了几个数值示例,以说明对MCDM和MCGDM问题的应用,以证明所提出方法的有效性。

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