An Uncertain Multiple-Criteria Choice Method on Grounds of T-Spherical Fuzzy Data-Driven Correlation Measures

Wang, Jih-Chang; Chen, Ting‐Yu

doi:10.15388/22-infor500

Cited by 1 publication

(11 citation statements)

References 56 publications

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“…The T-SF framework outperforms the intuitionistic, Pythagorean, Fermatean, and q-rung orthopair fuzzy models because it has a supplementary isolated function called neutrality-membership that strives to symbolize the abstinent viewpoint that does not feel inclined or willing to adopt either positive opinions (i.e., positivity-membership) or negative opinions (i.e., negativity-membership) (Chen 2022d ; Wang and Chen 2022 ). Due to a versatile axiomatic condition, the T-SF set has far broader contexts than the picture and spherical fuzzy sets and is better able to depict information space (Yang and Pang 2022 ; Zedam et al 2022 ).…”

Section: Literature Review and Research Vacanciesmentioning

confidence: 99%

“…Park et al ( 2021 ) studied a new preference relation and scoring function based on T-SF sets to yield consistent values in the ranking of available options and then established an algorithm to manage a practical issue of product quality assessment for online shopping platforms. Wang and Chen ( 2022 ) suggested using T-SF data-driven correlation measurements and comprehensive correlation indices to carry out the multiple-criteria evaluation for location selection. A convenient spatial C-means model in T-SF settings employing bias correction was utilized by Xian et al ( 2022 ) to enhance the performance of anti-noise and picture edge detection.…”

Section: Literature Review and Research Vacanciesmentioning

confidence: 99%

“…The T-SF configuration can enhance the restricted information space and broaden the spectrum of uncertainty representation for complex real-life scenarios. In practical applications for making judgments, T-SF sets provide a convenient and adaptable way to describe higher-order uncertainties and manage intricate fuzzy information (Wang and Chen 2022 ). In responding to complex actual situations, the T-SF configuration’s use results in superior information space representation (Chen 2022b , c ).…”

Section: Literature Review and Research Vacanciesmentioning

confidence: 99%

“…One of the long-established statistical measures for estimating linear relationships between quantitative objects is the notion of correlation coefficients (Riaz et al 2021 ; Varshney et al 2022 ; Wang and Chen 2022 ). There were several extended forms of correlation coefficients for the intensity of statistical relationships, depending on different kinds of equivocal and indistinct data in order to boost the usefulness of correlation coefficients within highly uncertain environments (Li et al 2022 ; Singh and Ganie 2022 ; Varshney et al 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, to illustrate the suitability and utility of their idea, Ali et al used the recommended correlation coefficient to address the pattern recognition issues in the practical decision-making arena. For an uncertain decision-making procedure featuring T-spherical fuzziness, Wang and Chen ( 2022 ) created an original multiple-criteria assessment approach utilizing a novel idea of T-SF data-driven correlation measurements. Wang and Chen further demonstrated how effectively the established solutions perform in T-SF uncertain conditions by utilizing an implementation for location selection.…”

Section: Introductionmentioning

confidence: 99%

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Multiple criteria decision analytic methods in management with T-spherical fuzzy information

Chen

2023

Artif Intell Rev

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With a focus on T-spherical fuzzy (T-SF) sets, the aim of this paper is to create a split-new appraisal mechanism and an innovative decision analytic method for use with multiple-criteria assessment and selection in uncertain situations. The T-SF frame is the latest recent advancement in fuzzy settings and uses four facets (consisting of membership grades of positivity, neutrality, negativity, and refusal) to elucidate complex uncertainties, thereby evidently reducing information loss, in anticipation of fully manifesting indistinct and equivocal information. This paper adds to the body of knowledge regarding multiple criteria choice modeling by raising T-SF correlation-oriented measurements connected to the fixed and displaced ideal/anti-ideal benchmarks and by creating an approachable appraisal mechanism for advancing a T-SF decision analytic methodology. Consider, in particular, the performance ratings of available options in terms of judging criteria under the T-SF type of uncertainties. This research gives correlation-oriented measurements focusing on two varieties of maximum and square root functions in T-SF situations, which serve as a solid foundation for an efficacious appraisal mechanism from two views of anchored judgments corresponding to the fixed and displaced benchmarks. The T-SF Minkowski distance index is generated to integrate the outranking and outranked identifiers relying on correlation-oriented measurements for figuring out the local outranking and outranked indices. The T-SF decision analytic procedures are constructed using a new appraisal significance index that is founded on certain valuable insights of correlation-oriented maximizing and minimizing indices as well as global outranking and outranked indices. Additionally, a concrete location selection dilemma is dealt with in this research to showcase the applicability and efficiency of the suggested T-SF decision analytic methodology. Sensitivity analyses and comparative studies are carried out to investigate substantial modifications in pertinent parameters and to confirm the robustness of the predominance relationships among the available options. The suggested approaches are adaptable, flexible, and reliable, according to the application outcomes and comparison findings. This research provides four scientific contributions: (1) the utilization of T-SF correlation coefficients as the basis for prioritization analysis involving multiple criteria assessments, (2) the evolution of the T-SF Minkowski distance index to model outranking decision-making processes, (3) the creation of a reliable appraisal mechanism based on T-SF correlation-oriented measurements for intelligent decision support, and (4) the advancement of computational tools and procedures (e.g., correlation-oriented maximizing and minimizing indices, global outranking and outranked indices, and appraisal significance indices) to perform the decision analytic procedure in T-SF settings. In terms of managerial implications, the solution findings support the employment of...

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