q-rung orthopair fuzzy 2-tuple linguistic clustering algorithm and its applications to clustering analysis

Abbas, Fatima; Ali, Jawad; Mashwani, Wali Khan; Syam, Muhammed I.

doi:10.1038/s41598-023-29932-y

Cited by 13 publications

(8 citation statements)

References 41 publications

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“…Li and his team [29] utilized a clustering analysis, as an illustration, to showcase the superiority of the proposed method by examining two δ-CC for q-rung orthopair fuzzy conditions. Abbas et.al [1] explores the clustering technique for q-ROF 2-tuple linguistic sets based on CC. Through the use of counter-examples, Lin [28] examines the inadequacies of the current CC and suggests a new directional correlation rate, as well as its weighted version for PFSs.…”

Section: A Literature Reviewmentioning

confidence: 99%

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Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Kannan,

Jayakumar,

Saeed

et al. 2024

IEEE Access

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The significance of clustering algorithms lies in their ability to distinguish problems and devise customized solutions. In the broader context of clustering, fuzzy clustering is one of the crucial aspects. In response to the real-world clustering problems, this research suggests a new fuzzy cluster scheme of data under the linear diophantine fuzzy set(LDFS) framework. More precisely, LDF clustering is initiated with the aid of the correlation coefficient(CC) and weighted correlation coefficient(WCC) for LDFS. Due to their ability to quantify the degree of similarity between two elements, CC are valuable in clustering problems. The LDF-clustering algorithm comprises a well-integrated algorithm for managing uncertainty and CC among LDFS. Also, our approach to LDF clustering is compared to existing fuzzy clustering studies to assess its effectiveness. Since LDFS broadens the score space, the experimental evaluation of our proposed scheme enables Decision makers(DM) to freely select their score values. The theme of this study is to impart the commencement of LDF-clustering analysis and attempt to apply CC to the clustering problem.An interpretative example provides the analysis of the logistic efficiency of food products by employing an LDF-clustering algorithm.

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Section: A Literature Reviewmentioning

confidence: 99%

“…The range of data limits the DM to certain bound Abbas et.al [1] q-ROF 2-tuple Clustering Algorithm based on q-ROF CC…”

Section: Vehicle Classificationmentioning

confidence: 99%

Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Kannan,

Jayakumar,

Saeed

et al. 2024

IEEE Access

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“…This score function is further extended to the IVq r OFN N as given in Equation ( 10) ∈ IVq r OFS. If we employ Equation (10) to N 5 and N 6 , then S Jag (N 5 ) = S Jag (N 6 ) = −0.0400. This implies N 5 = N 6 but N 5 N 6 .…”

Section: Comparison Rule Of Ivp Q R Ofnsmentioning

confidence: 99%

“…In this classification, IFSs, PyFSs, and FFSs are assigned the values of one, two, and three, respectively, for the parameter q. Following the emergence of this influential concept, several scholars were drawn to the study of q r OFSs and their applications in DM [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Interval-Valued p,q-Rung Orthopair Fuzzy Exponential TODIM Approach and Its Application to Green Supplier Selection

Ali,

Khan

2023

Symmetry

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An interval-valued q-rung orthopair fuzzy set (IVqrOFS) is a robust and esteemed model in managing imprecise information, utilizing a controllable parameter q≥1. Expanding its applicability, we propose a refinement to it, termed the interval-valued p,q-rung orthopair fuzzy set, denoted IVp,qrOFS. This advancement enables the handling of scenarios where varied assessment levels for membership and non-membership grades are necessary, a challenge unaddressed by existing extensions of interval-valued intuitionistic fuzzy sets. We establish the fundamental mathematical operations for the IVp,qrOFS and explore their key properties. To compare interval-valued p,q-rung orthopair fuzzy (IVp,qrOF) numbers, a novel score function is put forward and compared to the known IVqrOFS-based score functions to determine its viability. Moreover, we present IVp,qrOF aggregation operators (AOs), accompanied by rigorous proof of their essential characteristics, including boundedness, monotonicity, and symmetry. This study introduces the interaction of IVp,qrOF criteria through the inter-criteria correlation (CRITIC) approach. This method determines criteria weights based on the proposed distance measurements and the score function. The CRITIC method is integrated with the exponential TODIM approach (exp-TODIM), resulting in an innovative decision-making framework that is less susceptible to parameter fluctuations and showcases a high stability. An illustrative example of selecting a suitable supplier is provided to demonstrate the practical application of the developed exp-TODIM approach. Finally, a sensitivity analysis is conducted to exhibit the method’s stability, and a comparative analysis is performed to elucidate its strengths and advantages.

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“…iv). Numerous MCGDM approaches and their corresponding applications have been documented in the literature [ 39 , 61 , 62 ]. However, a noticeable gap exists regarding integrated approaches within the context of the q-RFL environment.…”

Section: Introductionmentioning

confidence: 99%

An integrated group decision-making method under q-rung orthopair fuzzy 2-tuple linguistic context with partial weight information

Abbas,

Ali,

Mashwani

et al. 2024

PLoS ONE

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Considering the advantages of q-rung orthopair fuzzy 2-tuple linguistic set (q-RFLS), which includes both linguistic and numeric data to describe evaluations, this article aims to design a new decision-making methodology by integrating Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and qualitative flexible (QUALIFLEX) methods based on the revised aggregation operators to solve multiple criteria group decision making (MCGDM). To accomplish this, we first revise the extant operational laws of q-RFLSs to make up for their shortcomings. Based on novel operational laws, we develop q-rung orthopair fuzzy 2-tuple linguistic (q-RFL) weighted averaging and geometric operators and provide the corresponding results. Next, we develop a maximization deviation model to determine the criterion weights in the decision-making procedure, which accounts for partial weight unknown information. Then, the VIKOR and QUALIFLEX methodologies are combined, which can assess the concordance index of each ranking combination using group utility and individual maximum regret value of alternative and acquire the ranking result based on each permutation’s general concordance index values. Consequently, a case study is conducted to select the best bike-sharing recycling supplier utilizing the suggested VIKOR-QUALIFLEX MCGDM method, demonstrating the method’s applicability and availability. Finally, through sensitivity and comparative analysis, the validity and superiority of the proposed method are demonstrated.

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q-rung orthopair fuzzy 2-tuple linguistic clustering algorithm and its applications to clustering analysis

Cited by 13 publications

References 41 publications

Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products

Interval-Valued p,q-Rung Orthopair Fuzzy Exponential TODIM Approach and Its Application to Green Supplier Selection

An integrated group decision-making method under q-rung orthopair fuzzy 2-tuple linguistic context with partial weight information

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