Measure-Based Group Decision-Making With Principle-Guided Social Interaction Influence for Incomplete Information: A Game Theoretic Perspective

Liu, Zeyi; Deng, Yong; Yager, Ronald R.

doi:10.1109/tfuzz.2021.3053324

Cited by 27 publications

(1 citation statement)

References 59 publications

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“…In the following years, the literature of FS theory was expanded by introducing many generalized versions of FSs such as the Pythagorean fuzzy set (PyFS) [3][4][5] and q-rung fuzzy set (q-ROFS). 6,7 By means of these set theories, the uncertainty was allowed to be described from different perspectives, and thus many issues including uncertainty such as decision making, [8][9][10][11][12][13] multiattribute decision making, [14][15][16][17] game theory, [18][19][20][21][22][23] medical diagnosis, [24][25][26] pattern recognition, [27][28][29] supplier-retailer inventory model, 30,31 economic order quantity model, 32,33 clustering analysis, 34,35 and supplier selection 36,37 were discussed. Smarandache 38 introduced the neutrosophic set, taking into account the degrees of membership, nonmembership, indeterminacy and hesitation simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Linguistic single‐valued neutrosophic soft sets with applications in game theory

Kamacı

2021

Int J Intell Syst

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The information based on the tripartite (truth, indeterminacy, and falsity) can be described by single‐valued neutrosophic numbers, but the linguistic information based on these tripartite cannot be represented by single‐valued neutrosophic numbers. To overcome this obstacle, linguistic single‐valued neutrosophic numbers are characterized independently by the truth, indeterminacy, and falsity linguistic variables. In this paper, some new operations are introduced to increase the richness of linguistic fusion based on the linguistic single‐valued neutrosophic approach. The Hamming distance‐based formula is proposed to measure the distance between two linguistic single‐valued neutrosophic numbers. Afterwards, we initiate the theory of linguistic single‐valued neutrosophic soft (LSVNS) set by combining linguistic single‐valued neutrosophic set and soft set. Meanwhile, the different computational functions and desirable properties of LSVNS sets are studied. Furthermore, we construct the framework of LSVNS technique for order preference by similarity to ideal solution (TOPSIS) and then present a game theory model based on this framework. Finally, we give an outstanding example to validate the practicality and effectiveness of the proposed LSVNS TOPSIS‐based game theory model.

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