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Group decision-making for the selection of an antivirus mask under fermatean fuzzy soft information
Journal of Intelligent & Fuzzy Systems ( IF 1.7 ) Pub Date : 2020-11-27 , DOI: 10.3233/jifs-201760
Gulfam Shahzadi 1 , Muhammad Akram 1
Affiliation  

With the rapid increase of COVID-19, mostly people are facing antivirus mask shortages. It is necessary to select a good antivirus mask and make it useful for everyone. For maximize the efficacy of the antivirus masks, we propose a decision support algorithm based on the concept of Fermatean fuzzysoft set (FFSfS). The basic purpose of this article is to introduce the notion of FFSfS to deal with problems involving uncertainty and complexity corresponding to various parameters. Here, the valuable properties of FFSfS are merged with the Yager operator to propose four new operators, namely, Fermatean fuzzy soft Yager weighted average (FFSfYWA), Fermatean fuzzy soft Yager ordered weighted average (FFSfYOWA), Fermatean fuzzy soft Yager weighted geometric (FFSfYWG) and Fermatean fuzzy soft Yager ordered weighted geometric (FFSfYOWG) operators. The fundamental properties of proposed operators are discussed. For the importance of proposed operators, a multi-attribute group decision-making (MAGDM) strategy is presented along with an application for the selection of an antivirus mask over the COVID-19 pandemic. The comparison with existing operators shows that existing operators cannot deal with data involving parametric study but developed operators have the ability to deal decision-making problems using parameterized information.

中文翻译:

在fermatean模糊软信息下选择防毒面具的小组决策

随着COVID-19的迅速增加,大多数人都面临着防病毒面具短缺的问题。有必要选择一个好的防病毒面具,并使它对每个人有用。为了最大程度地发挥防毒面具的功效,我们提出了基于Fermatean Fuzzysoft集(FFSfS)概念的决策支持算法。本文的基本目的是介绍FFSfS的概念,以处理涉及各种参数所涉及的不确定性和复杂性的问题。在此,将FFSfS的有价值的属性与Yager运算符合并,以提出四个新的运算符,分别是Fermatean模糊软Yager加权平均值(FFSfYWA),Fermatean模糊软Yager有序加权平均值(FFSfYOWA),Fermatean模糊软Yager加权几何(FFSfYWG) )和Fermatean模糊软Yager有序加权几何(FFSfYOWG)运算符。讨论了建议的算子的基本属性。考虑到提议的运营商的重要性,提出了一种多属性组决策(MAGDM)策略以及一种在COVID-19大流行中选择防毒面具的应用。与现有运营商的比较表明,现有运营商无法处理涉及参数研究的数据,但发达运营商具有使用参数化信息处理决策问题的能力。
更新日期:2020-11-27
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