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Granular Computing

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31.01.2022 | Original Paper

Multicriteria decision-making based on distance measures and knowledge measures of Fermatean fuzzy sets

verfasst von: Abdul Haseeb Ganie

Erschienen in: Granular Computing | Ausgabe 4/2022

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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.

Vorheriger Artikel Multiple attribute decision-making based on 3,4-quasirung fuzzy sets

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Titel: Multicriteria decision-making based on distance measures and knowledge measures of Fermatean fuzzy sets
verfasst von: Abdul Haseeb Ganie
Publikationsdatum: 31.01.2022
Verlag: Springer International Publishing
Erschienen in: Granular Computing / Ausgabe 4/2022
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI: https://doi.org/10.1007/s41066-021-00309-8

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