New Methods of Computing Correlation Coefficient Based on Pythagorean Fuzzy Information and Their Applications in Disaster Control and Diagnostic Analysis

Ejegwa, Paul Augustine; Sarkar, Arun; Onyeke, Idoko Charles

doi:10.1007/978-3-031-35668-1_21

Fuzzy Optimization, Decision-Making and Operations Research 2023

DOI: 10.1007/978-3-031-35668-1_21

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New Methods of Computing Correlation Coefficient Based on Pythagorean Fuzzy Information and Their Applications in Disaster Control and Diagnostic Analysis

Paul Augustine Ejegwa,

Arun Sarkar,

Idoko Charles Onyeke

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2024

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Cited by 3 publications

References 38 publications

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Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications

Aruchsamy,

Velusamy,

Dhandapani

et al. 2024

Journal of Mathematics

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The circular Fermatean fuzzy (CFF) set is an advancement of the Fermatean fuzzy (FF) set and the interval-valued Fermatean fuzzy (IVFF) set which deals with uncertainty. The CFF set is represented as a circle of radius ranging from 0 to 2 with the center at the degree of association (DA) and degree of nonassociation (DNA). If multiple people are involved in making decisions, the CFF set, as an alternative to the FF and IVFF sets, can deal with ambiguity more effectively by encircling the decision values within a circle rather than taking an average. Using algorithms, a pattern can be observed computationally or visually. Machine learning algorithm utilizes pattern recognition as an instrument for identifying patterns and also similarity measure (SM) is a beneficial pattern recognition tool used to classify items, discover variations, and make future predictions for decision making. In this work, we introduce the CFF cosine and Dice similarity measures (CFFDMs and CFFSMs), and their properties are studied. Unlike traditional approaches of decision making, which emphasize a single number, the proposed CFFSMs observe the pattern over the circular region to help in dealing with uncertainty more effectively. We introduce an innovative decision-making method in the FF setting. Available bank loans and applicants’ eligibility levels are represented as CFF set using their FF criteria and are taken as loan patterns and customer eligibility patterns. The loan is allocated to the applicant by measuring the CFFCSM and CFFDSM between the two patterns. Also, laptops are suggested to the customers by measuring the similarity between specification pattern and requirement pattern. The correctness and consistency of the proposed models are ensured by comparison analysis and graphical simulations of the input and similarity CFFNs.

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Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications

Aruchsamy,

Velusamy,

Dhandapani

et al. 2024

Journal of Mathematics

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Multi-Q Cubic Bipolar Fuzzy Soft Sets and Cosine Similarity Methods for Multi-Criteria Decision Making

Alqablan,

Alsager

2024

Symmetry

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This study introduces a novel mathematical tool for representing imprecise and ambiguous data: the multi-q cubic bipolar fuzzy soft set. Building upon established bipolar fuzzy sets and soft sets, this paper fist defines the concept of multi-q cubic bipolar fuzzy sets and their fundamental properties. Mathematical operations such as complement, union, and intersection are then developed for these sets. The core contribution lies in the introduction of multi-q cubic bipolar fuzzy soft sets. This new tool allows for a more nuanced representation of imprecise data compared to existing approaches. Key operations for manipulating these sets, including complement, restriction, and expansion, are defined. The applicability of multi-q cubic bipolar fuzzy soft sets extends to various domains, including multi-criteria decision making and problem solving. Illustrative examples demonstrate the practical utility of this innovative concept.

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A new similarity function for Pythagorean fuzzy sets with application in football analysis

Li,

Ejegwa,

et al. 2024

MATH

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<abstract><p>The idea of Pythagorean fuzzy sets (PFSs) has been extensively applied in various decision-making scenarios. Many of the applications of PFSs were carried out based on similarity functions. Some methods of similarity functions for PFSs (SFPFSs) cannot be trusted for a reliable interpretations in practical cases due to some of their setbacks. In this work, a new method of SFPFSs is developed with the capacity to outsmart the efficiency of the extant SFPFSs in terms of precise results and appropriately satisfying the rules of SFs. The new method is described with some results to validate the properties of SFs. In terms of practical application, we use the newly developed method of SFPFSs to discuss the relationship between the players of the Liverpool Football Club (FC) in the 2022/2023 English Premier League (EPL) season to assess their performances in their resurgent moments within the season. Using data from BBC Sport analysis (BBCSA) on the players' rating per match in a Pythagorean fuzzy setting, we establish the players' interactions, communications, passing, contributions, and performances to ascertain the high ranking players based on performances. Similarly, a comparative analyses are presented in tables to undoubtedly express the superiority of the newly developed method of SFPFSs. Due to the flexibility of the newly developed method of SFPFSs, it can be used for clustering analysis. In addition, the new method of SFPFSs can be extended to other uncertain environments other than PFSs.</p></abstract>

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New Methods of Computing Correlation Coefficient Based on Pythagorean Fuzzy Information and Their Applications in Disaster Control and Diagnostic Analysis

Cited by 3 publications

References 38 publications

Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications

Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications

Multi-Q Cubic Bipolar Fuzzy Soft Sets and Cosine Similarity Methods for Multi-Criteria Decision Making

A new similarity function for Pythagorean fuzzy sets with application in football analysis

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