Cubic Pythagorean Hesitant Fuzzy Linear Spaces and Its Relevance in Multi Criteria Decision Making

Gundeti Soujanya, P. Kavyasree, B. S. Reddy
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Abstract

Pythagorean fuzzy sets and interval valued Pythagorean fuzzy sets have an important role in decision making techniques. Pythagorean hesitant fuzzy sets are time and again used in dealing with uncertain and vague data. The motive of this paper is to introduce the notion cubic Pythagorean hesitant fuzzy linear spaces. We also present the notion of P(R)-intersection, P(R)-union of cubic Pythagorean hesitant fuzzy linear spaces with examples. Secondly, a series of operators like cubic Pythagorean hesitant fuzzy weighted averaging aggregation operators, cubic Pythagorean hesitant fuzzy order weighted averaging aggregation operators and cubic Pythagorean hesitant fuzzy hybrid order weighted averaging aggregation operators are developed. Then, these aggregation operators are further extended to cubic Pythagorean hesitant fuzzy prioritized weighted averaging aggregation operators by assigning priorities to the criteria. A real life MCDM problem has been illustrated and the effectiveness of the results are compared with those solved using cubic picture hesitant fuzzy prioritized weighted averaging aggregation operators.
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立方毕达哥拉斯犹豫模糊线性空间及其在多标准决策中的相关性
毕达哥拉斯模糊集和区间值毕达哥拉斯模糊集在决策技术中发挥着重要作用。毕达哥拉斯犹豫模糊集一再被用于处理不确定和模糊的数据。本文旨在介绍立方毕达哥拉斯犹豫模糊线性空间的概念。我们还举例介绍了立方毕达哥拉斯犹豫模糊线性空间的 P(R)-intersection 和 P(R)-union 概念。其次,我们提出了一系列算子,如立方毕达哥拉斯犹豫模糊加权平均聚合算子、立方毕达哥拉斯犹豫模糊阶加权平均聚合算子和立方毕达哥拉斯犹豫模糊混合阶加权平均聚合算子。然后,通过给标准分配优先级,将这些聚合算子进一步扩展为立方勾股犹豫模糊优先级加权平均聚合算子。我们举例说明了一个现实生活中的 MCDM 问题,并将结果的有效性与使用立方毕达哥拉斯犹豫模糊优先级加权平均聚合算子解决的问题进行了比较。
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来源期刊
CiteScore
1.30
自引率
10.00%
发文量
60
审稿时长
12 weeks
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