Q-rung orthopair fuzzy sets and their variants
Mahalakshmi Pethaperumal; Vimala Jeyakumar; Jeevitha Kannan; Ashma Banu
Abstract
The q-Rung Orthopair Fuzzy set (qROF-set) environment is a contemporary tool for handling uncertainty and vagueness in decision-making scenarios. In this paper, we delve into the algebraic examination of q-rung orthopair Multi-Fuzzy Sets (MFSs) and explore their operational laws. The novel q-Rung Orthopair ...
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The q-Rung Orthopair Fuzzy set (qROF-set) environment is a contemporary tool for handling uncertainty and vagueness in decision-making scenarios. In this paper, we delve into the algebraic examination of q-rung orthopair Multi-Fuzzy Sets (MFSs) and explore their operational laws. The novel q-Rung Orthopair Multi-Fuzzy subgroup (qROMF-subgroup) is the extension of Intuitionistic Multi-Fuzzy Subgroup (IMF-subgroup) to encompass the domain of groups. The properties of the proposed fuzzy subgroup are examined in detail, and the paper concludes by defining two additional concepts: qROMF-coset and qROMF-normal subgroup. Finally, we present a comparison of the newly introduced model with existing approaches to validate its superior performance.
Q-rung orthopair fuzzy sets and their variants
Mujahid Abbas; Muhammad Waseem Asghar; Yanhui Guo
Abstract
The q-Rung Orthopair Fuzzy Soft Set (q-ROFSS) theory is a significant extension of Pythagorean fuzzy soft set and intuitionistic fuzzy soft set theories for dealing with the imprecision and uncertainty in data. The purpose of this study is to improve and apply this theory in decision-making. To achieve ...
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The q-Rung Orthopair Fuzzy Soft Set (q-ROFSS) theory is a significant extension of Pythagorean fuzzy soft set and intuitionistic fuzzy soft set theories for dealing with the imprecision and uncertainty in data. The purpose of this study is to improve and apply this theory in decision-making. To achieve this purpose, we firstly propose some Bonferroni Mean (BM) and Weighted Bonferroni Mean (WBM) aggregation operators for aggregating the data. Some desired properties are presented in detail and the existing aggregation operators are used as distinct cases of our proposed operators. Further, a decision-making analysis is presented based on our proposed operations and applied to decision-making in COVID-19 diagnosis. The preferred way is discussed to protect maximum human lives from COVID-19. A numerical example is given to support the claim. The experimental results demonstrate the proposed operators have an ability to make a precise decision with imprecision and uncertain information which will find a broad application in the decision-making area.
