Evidence map›Paper›PMID 39054307›Full record

ArticleScientific reports2024

Novel similarity measures under complex pythagorean fuzzy soft matrices and their application in decision making problems.

Muhammad Zeeshan, Madad Khan, Ramsha Shafqat, Ali Althobaiti, Saad Althobaiti, Tola Bekene Bedada

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In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Muhammad ZeeshanDepartment of Mathematics, The University of Agriculture, Dera Ismail Khan, Pakistan.
Madad KhanDepartment of Mathematics, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan.
Ramsha ShafqatDepartment of Mathematics and Statistics, The University of Lahore, Sargodha, 40100, Pakistan.
Ali AlthobaitiDepartment of Mathematics, College of Science, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia.
Saad AlthobaitiDepartment of Sciences and Technology, Ranyah University Collage, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia.
Tola Bekene BedadaDepartment of Mathematics, Wachemo University, Hosaina , Ethiopia. tolaB@wcu.edu.et.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complex fuzzy soft matrices play a crucial role in various applications, including decision-making, pattern recognition, signals processing, and image processing. The main objective of this study is to introduce the unique notions of complex Pythagorean fuzzy soft matrices (CPFSMs), which provide more flexibility and accuracy in modelling uncertainty. CPFSMs incorporate Pythagorean fuzzy soft matrices, allowing for more sophisticated uncertainty modeling. The key findings of CPFSMs, specific instances, and certain fundamental set-theoretic operations and principles were covered. A set of new distance metrics between two CPFSMs has been defined. In the context of complex Pythagorean fuzzy soft sets and complex Pythagorean fuzzy soft matrices, we created a CPFS decision-making technique. Moreover, the application's numerical example and comparison analysis have been effectively demonstrated. Thus, by integrating the concepts of Pythagorean fuzzy sets, soft matrices, and complex numbers, CPFSMs provide a robust framework with membership and non-membership degrees for complex decision-making modeling and analyzing uncertain data.

Indexed as

Complex Pythagorean fuzzy soft matricesComplex Pythagorean soft setDecision-makingSoft set

Identifiers

PMID39054307
PMCPMC11272792

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