Fermatean fuzzy Archimedean Heronian Mean-Based Model for estimating sustainable urban transport solutions

Kakati, Pankaj; Senapati, Tapan; Moslem, Sarbast; Pilla, Francesco

doi:10.1016/j.engappai.2023.107349

Cited by 27 publications

(1 citation statement)

References 69 publications

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“…Many researchers worked a lot in decision-making environments, and the following literature is discussed in Refs. [ [32] , [33] , [34] , [35] , [36] ].…”

Section: Introductionmentioning

confidence: 99%

Multi-attribute decision-making method based on complex T-spherical fuzzy frank prioritized aggregation operators

Rizwan khan,

Ullah,

Raza

et al. 2024

Heliyon

Self Cite

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“…Many researchers worked a lot in decision-making environments, and the following literature is discussed in Refs. [ [32] , [33] , [34] , [35] , [36] ].…”

Section: Introductionmentioning

confidence: 99%

Multi-attribute decision-making method based on complex T-spherical fuzzy frank prioritized aggregation operators

Rizwan khan,

Ullah,

Raza

et al. 2024

Heliyon

Self Cite

View full text Add to dashboard Cite

Fermatean fuzzy sets and its extensions: a systematic literature review

Büyüközkan,

Uztürk,

Ilıcak

2024

Artif Intell Rev

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The Fermatean Fuzzy Set (FFS) theory emerges as a crucial and prevalent tool in addressing uncertainty across diverse domains. Despite its recognized utility in managing ambiguous information, recent research lacks a comprehensive analysis of key FFS areas, applications, research gaps, and outcomes. This study, conducted through the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol, delves into an exploration of the FFS literature, reviewing 135 relevant articles. The documents are meticulously analyzed based on their integrated methodologies, Aggregation Operators (AOs), linguistic sets, and extensions. Additionally, a thematic analysis, facilitated by the Bibliometrix tool, is presented to provide nuanced insights into future research directions and crucial areas within the literature. The study unveils valuable findings, including the integration of linguistic variables with interval-valued FFS, fostering robust environments for dynamic decision-making—a mere glimpse of the potential directions for future research. The gaps and future directions section further articulates recommendations, offering a structured foundation for researchers to enhance their understanding of FFS and chart future studies confidently.

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New covering techniques and applications utilizing multigranulation fuzzy rough sets

Atef,

Liu,

Moslem

et al. 2024

Artif Intell Rev

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In order to conduct an in-depth study of Zhan’s methodology pertaining to the covering of multigranulation fuzzy rough sets ($$\hbox {C}_{{MG}}$$ C MG FRSs), we build two families: the family of fuzzy $$\beta $$ β -minimum descriptions and the family of $$\beta $$ β -maximum descriptions. Subsequently, utilizing these notions, we proceed to develop two variations of covering via optimistic (pessimistic) multigranuation rough set samples ($$\hbox {CO(P)}_{{MG}}$$ CO(P) MG FRS). The axiomatic properties are examined. In this study, we examine four models of covering using variable precision multigranulation fuzzy rough sets ($$\hbox {CVP}_{{MG}}$$ CVP MG FRSs). We proceed with analyzing the features of these models. Interconnections between these planned plans are also elucidated. This study explores algorithms that aim to identify innovative strategies for addressing multiattribute group decision-making problems (MAGDM) and multicriteria group decision-making problems (MCGDM). The test examples have been elucidated to provide an inclusive grasp of the efficacy of the offered samples. Ultimately, the distinctions between our methodologies and the preexisting research have been demonstrated.

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Fermatean fuzzy Archimedean Heronian Mean-Based Model for estimating sustainable urban transport solutions

Cited by 27 publications

References 69 publications

Multi-attribute decision-making method based on complex T-spherical fuzzy frank prioritized aggregation operators

Multi-attribute decision-making method based on complex T-spherical fuzzy frank prioritized aggregation operators

Fermatean fuzzy sets and its extensions: a systematic literature review

New covering techniques and applications utilizing multigranulation fuzzy rough sets

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