Evidence map›Paper›PMID 39209940›Full record

ArticleScientific reports2024

Various distance between generalized Diophantine fuzzy sets using multiple criteria decision making and their real life applications.

Murugan Palanikumar, Nasreen Kausar, Dragan Pamucar, Vladimir Simic, Fikadu Tesgera Tolasa

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Murugan PalanikumarDepartment of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, India.
Nasreen KausarDepartment of Mathematics, Faculty of Arts and Science, Yildiz Technical University, Esenler, Istanbul, 34220, Turkey.
Dragan PamucarDepartment of Operations Research and Statistics, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia.
Vladimir SimicFaculty of Transportation and Traffic Engineering, University of Belgrade, Vojvode Stepe 30, Belgrade, 11010, Serbia.
Fikadu Tesgera TolasaDepartment of Mathematics, Dambi Dollo University, Dambi dollo, Oromia, Ethiopia. fikadu@dadu.edu.et.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper describes a generalized Diophantine fuzzy sets, which can be seen as a generalization of both Diophantine fuzzy sets and Pythagorean fuzzy sets. We define the basic properties of generalized Diophantine fuzzy set, as well as their relationships and distances. We compare Diophantine fuzzy sets with other Diophantine Pythagorean fuzzy sets to demonstrate their importance in the literature. We introduce new operators including necessity, possibility, accuracy function and score function. Furthermore, we discuss the new distance between normalized Euclidean distance and normalized Hamming distance. For a generalized Diophantine fuzzy relation, image and inverse image functions are defined. Numerous real-world applications can be found for the prevalent ideas of intuitionistic fuzzy sets, Pythagorean fuzzy sets, Diophantine fuzzy sets and q-rung orthopair fuzzy sets. Regretfully, these theories about the membership and non-membership grades have their own limits. We provide a new idea the generalized Diophantine fuzzy set that eliminates these limitations by including reference parameters. Compared to other kinds of fuzzy sets, there are more applications for generalized Diophantine fuzzy sets. We offer practical examples that show how different enhanced distances might be used in everyday situations. Additionally, to demonstrate the effectiveness of the suggested approach, flowchart based multi-criteria decision-making is provided and used to a numerical example. The outcomes are assessed for various parameter values. Furthermore, a comparative analysis developed to demonstrate the superiority of the suggested technique over current methodologies.

Indexed as

Decision makingDiophantine generalized fuzzy relationEuclidean distanceHamming distance

Identifiers

PMID39209940
PMCPMC11362317

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