An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis

Thảo, Nguyễn Xuân; Ali, Mumtaz; Smarandache, Florentín

doi:10.3233/jifs-181084

Cited by 62 publications

(44 citation statements)

References 18 publications

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“… The proposed method has a better performance index when compared with the methods discussed in References [27,30–33,45]. The proposed method incorporates the complete parameters of IFS to minimize error of computation unlike the methods in References [27,32,33,45]. The proposed method is consistent with the axiomatic description of CCIFSs from statistical perspective unlike 27,30–33,45 …”

Section: Applicative Examplesmentioning

confidence: 87%

“…Liu et al 32 developed a new CCIFSs method using intuitionistic fuzzy deviation, variance and covariance with applications. Thao et al 33 proposed a different CCIFSs method with the same approach in Reference [32]. Garg and Kumar 34 presented a CCIFSs method on the basis of set pair analysis and used it to solve MCDM problems.…”

Section: Introductionmentioning

confidence: 99%

“…appraise the performances of the methods in References [27,30–33,45] for calculating CCIFSs and thus, introduce the intuitionistic fuzzy statistical correlation algorithm which shows precision and consistency in measuring CCIFSs.…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge, no existing method of computing correlation coefficient of IFSs adopts algorithmic approach coded with programming language. Therefore this paper is aimed at developing a new algorithmic CCIFSs technique via intuitionistic fuzzy mean, variance and covariance with a better output and interpretation when compare to the statistical CCIFSs methods in References [27,[30][31][32][33]45]. This novel statistical method of computing CCIFSs is coded with JAVA programming language for accurate and easy computations.…”

Section: Introductionmentioning

confidence: 99%

“…EJEGWA AND ONYEKE | 1387 (i) appraise the performances of the methods in References [27,[30][31][32][33]45] for calculating CCIFSs and thus, introduce the intuitionistic fuzzy statistical correlation algorithm which shows precision and consistency in measuring CCIFSs. (ii) mathematically prove the consistency of the novel method with the axiomatic description of statistical CCIFSs.…”

Section: Introductionmentioning

confidence: 99%

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Intuitionistic fuzzy statistical correlation algorithm with applications to multicriteria‐based decision‐making processes

Ejegwa

Onyeke

2020

Int J Intell Syst

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Intuitionistic fuzzy set is a significance soft computing tool for curbing fuzziness embedded in decisionmaking processes. To enhance the applicability of intuitionistic fuzzy sets in modelling practical real-life problems, various computing methods have been proposed like distance measures, similarity measures and correlation measures. This paper proposes an intuitionistic fuzzy statistical correlation algorithm with applications to pattern recognition and diagnostic processes. This novel method assesses the magnitude of relationship and indicates whether the intuitionistic fuzzy sets under consideration are correlated in either positive or negative sense. We substantiate the proposed technique with some theoretical results and numerically validate it to be superior in terms of accuracy and reliability in contrast to some hitherto techniques. Finally, we determine decision-making processes involving pattern recognition and diagnostic processes by using JAVA programming language to code the intuitionistic fuzzy statistical correlation measure.

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Section: Applicative Examplesmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Intuitionistic fuzzy statistical correlation algorithm with applications to multicriteria‐based decision‐making processes

Ejegwa

Onyeke

2020

Int J Intell Syst

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Performance of exponential similarity measures in supply of commodities in containment zones during COVID‐19 pandemic under Pythagorean fuzzy sets

Arora

Naithani

2022

Int J of Intelligent Sys

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Following the breakout of the novel coronavirus disease 2019 (COVID‐19), the government of India was forced to prohibit all forms of human movement. It became important to establish and maintain a supply of commodities in hotspots and containment zones in different parts of the country. This study critically proposes new exponential similarity measures to understand the requirement and distribution of commodities to these zones during the rapid spread of novel coronavirus (COVID‐19) across the globe. The primary goal is to utilize the important aspect of similarity measures based on exponential function under Pythagorean fuzzy sets, proposed by Yager. The article aims at finding the most required commodity in the affected areas and ensures its distribution in hotspots and containment zones. The projected path of grocery delivery to different residences in containment zones is determined by estimating the similarity measure between each residence and the various necessary goods. Numerical computations have been carried out to validate our proposed measures. Moreover, a comparison of the result for the proposed measures has been carried out to prove the efficacy.

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Pattern Recognition Based on an Improved Szmidt and Kacprzyk’s Correlation Coefficient in Pythagorean Fuzzy Environment

Ejegwa

Feng

Zhang

2020

Advances in Neural Networks – ISNN 2020

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An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis

Cited by 62 publications

References 18 publications

Intuitionistic fuzzy statistical correlation algorithm with applications to multicriteria‐based decision‐making processes

Intuitionistic fuzzy statistical correlation algorithm with applications to multicriteria‐based decision‐making processes

Performance of exponential similarity measures in supply of commodities in containment zones during COVID‐19 pandemic under Pythagorean fuzzy sets

Pattern Recognition Based on an Improved Szmidt and Kacprzyk’s Correlation Coefficient in Pythagorean Fuzzy Environment

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