2019
DOI: 10.3390/sym11020289
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A Generalized Approach towards Soft Expert Sets via Neutrosophic Cubic Sets with Applications in Games

Abstract: Games are considered to be the most attractive and healthy event between nationsand peoples. Soft expert sets are helpful for capturing uncertain and vague information.By contrast, neutrosophic set is a tri-component logic set, thus it can deal with uncertain,indeterminate, and incompatible information where the indeterminacy is quantified explicitly andtruth membership, indeterminacy membership, and falsity membership independent of each other.Subsequently, we develop a combined approach and extend this conce… Show more

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Cited by 9 publications
(4 citation statements)
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“…Jun et al [11] gave the idea of the NCS. For application of NCSs, we refer to [12][13][14][15][16][17]. In 2017, the concept of stable cubic sets was introduced by Muhiuddin et al [18].…”
Section: Introductionmentioning
confidence: 99%
“…Jun et al [11] gave the idea of the NCS. For application of NCSs, we refer to [12][13][14][15][16][17]. In 2017, the concept of stable cubic sets was introduced by Muhiuddin et al [18].…”
Section: Introductionmentioning
confidence: 99%
“…In the soft games, both the strategy sets and soft payoffs are crisp. For further development of the soft games, the fuzzy soft games [45], intuitionistic fuzzy soft games [46], neutrosophic fuzzy soft games [47], linguistic single-valued neutrosophic soft game [48], simplified neutrosophic multiplicative soft game [49], and neutrosophic cubic soft expert sets based game [50] were introduced. All of these soft game theory models are based on the single-attribute (S-A) function (see Table 1).…”
Section: Introductionmentioning
confidence: 99%
“…Further, the development made by different researchers in the area of cubic sets and their applications can be seen in [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47]. The idea of similarity measure was examined as the powerful mechanism used for many years in various fields using these given sets.…”
Section: Introductionmentioning
confidence: 99%