Some Fuzzy Logic Operators for Picture Fuzzy Sets

Cường, Bùi Công; Hai, Pham Van

doi:10.1109/kse.2015.20

Cited by 142 publications

(91 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper picture fuzzy theory have been continuously constructed with proposing the concepts which be extended from fuzzy cases: picture fuzzy negators N and the representation theory on them, picture fuzzy t-norms T , picture fuzzy t-conorms S. In the our paper [7,8] some new properties of an involutive fuzzy negator and some corresponding De Morgan picture fuzzy triples have been presented. In this paper some classifications of reprentable picture t-norms operators and picture t-conorms operators are defined.…”

Section: Discussionmentioning

confidence: 99%

“…Then new operators of picture fuzzy sets were presented with many properties were given in [5,6]. In [7], we have introduced picture fuzzy logic connectives and some properties of picture fuzzy sets. In this paper, we will study some classifications of representable picture fuzzy t-norms and picture fuzzy t-conorms on picture fuzzy sets.…”

Section: Introductionmentioning

confidence: 99%

“…Some results of the classifications of fuzzy logics operators for fuzzy sets are given in [3,4]. In 2013, we defined the picture fuzzy sets [5,6] and in 2015 some representable t-norms operators and t-conorms operators were defined and firstly were presented in [7,8]. In this paper, we will investigate the classification of representable picture t-norms and picture t-conorms operators for picture fuzzy sets.…”

mentioning

confidence: 99%

See 2 more Smart Citations

A classification of representable t-norm operators for picture fuzzy sets

Cường

Kreinovitch

Ngan

2016

2016 Eighth International Conference on Knowledge and Systems Engineering (KSE)

Self Cite

View full text Add to dashboard Cite

Abstract-T-norms and t-conorms are basic operators of fuzzy logics. The classifications of these operators are significant problems. Some results of the classifications of fuzzy logics operators for fuzzy sets are given in [3,4]. In 2013, we defined the picture fuzzy sets [5,6] and in 2015 some representable t-norms operators and t-conorms operators were defined and firstly were presented in [7,8]. In this paper, we will investigate the classification of representable picture t-norms and picture t-conorms operators for picture fuzzy sets.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

A classification of representable t-norm operators for picture fuzzy sets

Cường

Kreinovitch

Ngan

2016

2016 Eighth International Conference on Knowledge and Systems Engineering (KSE)

Self Cite

View full text Add to dashboard Cite

show abstract

“…In order not to cause confusion, the type-2 order relation on D* is denoted by "≤ 2 ", it is different from [30].…”

Section: On Inclusion Relation Of Picture Fuzzy Relationsmentioning

confidence: 99%

“…Thus, in 2013, B. C. Cuong proposed a new concept named picture fuzzy sets (PFSs) [28][29][30], which is an extension of fuzzy sets and intuitionistic fuzzy sets. Picture fuzzy sets give three degrees of an element named degree of positive membership, degree of neutral membership and degree of negative membership, respectively.…”

Section: Introductionmentioning

confidence: 99%

New Operations of Picture Fuzzy Relations and Fuzzy Comprehensive Evaluation

Zhang

2017

Symmetry

View full text Add to dashboard Cite

Abstract:In this paper, some new operations and basic properties of picture fuzzy relations are intensively studied. First, a new inclusion relation (called type-2 inclusion relation) of picture fuzzy relations is introduced, as well as the corresponding type-2 union, type-2 intersection and type-2 complement operations. Second, the notions of anti-reflexive kernel, symmetric kernel, reflexive closure and symmetric closure of a picture fuzzy relation are introduced and their properties are explored. Moreover, a new method to solve picture fuzzy comprehensive evaluation problems is proposed by defining the new composition operation of picture fuzzy relations, and the picture fuzzy comprehensive evaluation model is built. Finally, an application example (about investment risk) of picture fuzzy comprehensive evaluation is given, and the effective experiment results are obtained.

show abstract

Generalized MULTIMOORA method and Dombi prioritized weighted aggregation operators based on T‐spherical fuzzy sets and their applications

Mahmood

Warraich

Ali

et al. 2021

Int J of Intelligent Sys

View full text Add to dashboard Cite

In this manuscript, the technique of the generalized MULTIMOORA method is investigated by using the concept of a T‐spherical fuzzy set (T‐SFS), which is the modified idea of a picture fuzzy set to handle awkward and vague information in daily life problems. T‐SFS covers the degree of truth, abstinence, and falsity with a rule that the sum of the qth‐powers of all degrees is restricted to the unit interval. Moreover, for examining the interrelationships among any number of T‐SFSs, we construct the idea of T‐spherical fuzzy Dombi prioritized weighted arithmetic (T‐SFDPWA) aggregation operators, T‐spherical fuzzy Dombi prioritized arithmetic, T‐spherical fuzzy Dombi prioritized geometric, and T‐spherical fuzzy Dombi prioritized weighted geometric (T‐SFDPWG) aggregation operators are given. Then, the basic properties of T‐SFDPWA and T‐SFDPWG aggregation operators are investigated and discussed in some of their cases. The investigated operators based on T‐SFS are utilized in the environment of multiattribute decision‐making problems to find the consistency and proficiency of the developed operators. In last, we illustrated some numerical examples based on explored operators is to examine the reliability and validity of the investigated operators with the help of comparative analysis and graphical representations with some existing ideas to show the presented approaches are extensive powerful.

show abstract

Some Fuzzy Logic Operators for Picture Fuzzy Sets

Cited by 142 publications

References 11 publications

A classification of representable t-norm operators for picture fuzzy sets

A classification of representable t-norm operators for picture fuzzy sets

New Operations of Picture Fuzzy Relations and Fuzzy Comprehensive Evaluation

Generalized MULTIMOORA method and Dombi prioritized weighted aggregation operators based on T‐spherical fuzzy sets and their applications

Contact Info

Product

Resources

About