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Entropy on interval-valued intuitionistic fuzzy sets and its application in multi-attribute decision making

机译:区间直觉模糊集的熵及其在多属性决策中的应用

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This article proposes a new axiomatic definition of entropy on interval-valued intuitionistic fuzzy sets (IVIFSs) and a method to construct different entropies on IVIFSs. Furthermore, a new multi-attribute decision making (MADM) method based on similarity measures using entropy-based attribute weights is proposed to deal with the decision making situations where the alternatives on attributes are expressed by IVIFSs and the attribute weights information is unknown. Instead of using traditional fuzzy entropy, which obtain attribute weights through the probabilistic discrimination of attributes, we utilize the interval-valued intuitionistic fuzzy (IVIF) entropy to assess attribute weights based on the credibility of the IVIF decision making matrix. Finally, two numerical examples are given to demonstrate the feasibility and validity of the newly proposed MADM method, by comparing it with other fuzzy MADM methods.
机译:本文提出了区间值直觉模糊集(IVIFS)上熵的公理化定义,以及一种在IVIFS上构造不同熵的方法。此外,提出了一种新的基于相似性度量的多属性决策方法,该方法使用基于熵的属性权重来处理由IVIFS表示属性替代项且属性权重信息未知的决策情况。代替使用通过属性的概率判别获得属性权重的传统模糊熵,我们利用区间值直觉模糊(IVIF)熵,基于IVIF决策矩阵的可信度来评估属性权重。最后,通过两个数值例子,通过与其他模糊MADM方法进行比较,证明了新提出的MADM方法的可行性和有效性。

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