ArticleGranular computing2022
Multicriteria decision-making based on distance measures and knowledge measures of Fermatean fuzzy sets.
Article in Granular computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Optimizing decision making with Fermatean fuzzy soft Hamachar operators in the analysis of anaphylaxis (a life-threatening allergic reaction).Scientific reports · 2026Article
- Advancing decision making with distance and similarity measures for belief and plausibility in Fermatean fuzzy sets.Scientific reports · 2025Article
- Fermatean fuzzy score function and distance measure based group decision making framework for household waste recycling plant location selection.Scientific reports · 2024Article
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1 author.
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Abstract
Fermatean fuzzy sets are more powerful than fuzzy sets, intuitionistic fuzzy sets, and Pythagorean fuzzy sets in handling various problems involving uncertainty. The distance measures in the fuzzy and non-standard fuzzy frameworks have got their applicability in various areas such as pattern analysis, clustering, medical diagnosis, etc. Also, the fuzzy and non-standard fuzzy knowledge measures have played a vital role in computing the criteria weights in the multicriteria decision-making problems. As there is no study concerning the distance and knowledge measures of Fermatean fuzzy sets, so in this paper, we propose some novel distance measures for Fermatean fuzzy sets using t-conorms. We also discuss their various desirable properties. With the help of suggested distance measures, we introduce some knowledge measures for Fermatean fuzzy sets. Through numerical comparison and linguistic hedges, we establish the effectiveness of the suggested distance measures and knowledge measures, respectively, over the existing measures in the Pythagorean/Fermatean fuzzy setting. At last, we demonstrate the application of the suggested measures in pattern analyis and multicriteria decision-making.
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