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首页> 外文期刊>Journal of information and computational science >Normalized Geometric Bonferroni Operators of Hesitant Fuzzy Sets and Their Application in Multiple Attribute Decision Making
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Normalized Geometric Bonferroni Operators of Hesitant Fuzzy Sets and Their Application in Multiple Attribute Decision Making

机译:犹豫模糊集的规范化几何Bonferroni算子及其在多属性决策中的应用

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摘要

The Bonferroni Mean (BM) is a very useful aggregation technique, because it can capture the interrelation-ship between input arguments. Many BM type operators have been proposed, such as the weighted BM, the generalized BM, the intuitionistic fuzzy BM, and so on. However, the geometric BM for Hesitant Fuzzy Sets (HFSs) hasn't been studied. In this paper, based on the geometric mean and the BM, we will propose two normalized weighted geometric BMs, and they can reflect the interrelationship between the individual criterion and other criterion, which is the main advantage of the BM. Then, we will study some properties of the proposed operators, and apply them to deal with Multiple Attribute Decision Making (MADM) problems under the hesitant fuzzy environments. Finally, an example is presented to verify the developed approach.
机译:Bonferroni均值(BM)是一种非常有用的聚合技术,因为它可以捕获输入参数之间的相互关系。提出了许多BM类型算子,如加权BM,广义BM,直觉模糊BM等。但是,尚未研究犹豫模糊集(HFS)的几何BM。本文在几何均值和BM的基础上,提出了两种归一化的加权几何BM,它们可以反映个体准则与其他准则之间的相互关系,这是BM的主要优点。然后,我们将研究拟议的算子的一些性质,并将其用于在犹豫的模糊环境下处理多属性决策(MADM)问题。最后,给出一个例子来验证所开发的方法。

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