Evidence map›Paper›PMID 39634419›Full record

ArticleHeliyon2024

A new Fermatean fuzzy Spearman-like correlation coefficient and its application in evaluating insecurity problem via multi-criteria decision-making approach.

Paul Augustine Ejegwa, Nasreen Kausar, Nezir Aydin, Yuming Feng, Oludolapo Akanni Olanrewaju

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Article in Heliyon, 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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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Paul Augustine EjegwaDepartment of Mathematics, Joseph Sarwuan Tarka University, Makurdi, Nigeria.
Nasreen KausarDepartment of Mathematics, Faculty of Arts and Science, Yildiz Technical University, Esenler 34220, Istanbul, Turkiye.
Nezir AydinCollege of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Yuming FengKey Laboratory of Intelligent Information Processing and Control, Chongqing Three Gorges University, Chongqing 404100, China.
Oludolapo Akanni OlanrewajuDepartment of Industrial Engineering, Durban University of Technology, Durban 4001, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The problem of insecurity is a global crisis with adverse effects on lives and properties. Fermatean fuzzy correlation coefficient is a dependable method for handling imprecision, which is the main bottleneck of insecurity assessment. A number of Fermatean fuzzy correlation coefficient methods have been developed. Based on Spearman's correlation coefficient, an innovative Fermatean fuzzy correlation coefficient method is built to enhance trustworthy insecurity assessment. The existing Fermatean fuzzy correlation coefficient methods are evaluated, and their shortcomings are identified in order to validate the construction of a new Fermatean fuzzy correlation coefficient method. The drawbacks of the existing methods lead us into building a new Fermatean fuzzy correlation coefficient method by using the Spearman's correlation coefficient approach, which has the potential of overcoming the drawbacks of the existing Fermatean fuzzy correlation coefficient methods. In addition, some theoretical findings are provided to support the strength of the novel Fermatean fuzzy correlation coefficient method and it is shown that the new method satisfies the Fermatean fuzzy correlation coefficient requirements. Furthermore, the novel Fermatean fuzzy correlation coefficient method is applied to assess the insecurity situation in the North-Central Region of Nigeria to furnish intended tourists with relevant travel advice. To demonstrate the inherent significance of the novel Fermatean fuzzy correlation coefficient method, we compare its effectiveness to that of the extant Fermatean fuzzy correlation coefficient methods. The results of the comparison show the superiority of the novel Fermatean fuzzy correlation coefficient method over the existing ones in terms of reliability, consistency, precision and compliance with the Fermatean fuzzy correlation coefficient axioms. Ultimately, it is discovered that the new method can effectively address hesitations related to insecurity assessment.

Indexed as

Correlation coefficientFermatean fuzzy setsInsecurity assessmentMulti-criteria decision-makingNorth central region of NigeriaSecurity crises

Identifiers

PMID39634419
PMCPMC11616503

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