Senapati Tapan, Chen Guiyun, Mesiar Radko, Saha Abhijit
School of Mathematics and Statistics, Southwest University, Beibei, 400715 Chongqing China.
Faculty of Civil Engineering, Slovak University of Technology, Radlinského 11, 810 05 Bratislava, Slovakia.
J Ambient Intell Humaniz Comput. 2022 Aug 11:1-15. doi: 10.1007/s12652-022-04360-4.
A useful expansion of the intuitionistic fuzzy set (IFS) for dealing with ambiguities in information is the Pythagorean fuzzy set (PFS), which is one of the most frequently used fuzzy sets in data science. Due to these circumstances, the Aczel-Alsina operations are used in this study to formulate several Pythagorean fuzzy (PF) Aczel-Alsina aggregation operators, which include the PF Aczel-Alsina weighted average (PFAAWA) operator, PF Aczel-Alsina order weighted average (PFAAOWA) operator, and PF Aczel-Alsina hybrid average (PFAAHA) operator. The distinguishing characteristics of these potential operators are studied in detail. The primary advantage of using an advanced operator is that it provides decision-makers with a more comprehensive understanding of the situation. If we compare the results of this study to those of prior strategies, we can see that the approach proposed in this study is more thorough, more precise, and more concrete. As a result, this technique makes a significant contribution to the solution of real-world problems. Eventually, the suggested operator is put into practise in order to overcome the issues related to multi-attribute decision-making under the PF data environment. A numerical example has been used to show that the suggested method is valid, useful, and effective.
用于处理信息模糊性的直觉模糊集（IFS）的一种有用扩展是毕达哥拉斯模糊集（PFS），它是数据科学中最常用的模糊集之一。鉴于这些情况，本研究使用阿泽尔 - 阿尔西纳运算来制定几种毕达哥拉斯模糊（PF）阿泽尔 - 阿尔西纳聚合算子，其中包括PF阿泽尔 - 阿尔西纳加权平均（PFAAWA）算子、PF阿泽尔 - 阿尔西纳有序加权平均（PFAAOWA）算子和PF阿泽尔 - 阿尔西纳混合平均（PFAAHA）算子。详细研究了这些潜在算子的显著特征。使用先进算子的主要优点是它能为决策者提供对情况更全面的理解。如果将本研究的结果与先前策略的结果进行比较，我们可以看到本研究提出的方法更全面、更精确且更具体。因此，该技术对解决实际问题做出了重大贡献。最后，为克服PF数据环境下多属性决策相关问题，将所提出的算子付诸实践。已使用一个数值示例表明所提出的方法是有效、有用且高效的。
