In this paper, a new Fuzzy Set (FS) ranking method (for type-1 and interval type-2 FSs), which is based on the Dempster-Shafer Theory (DST) of evidence with fuzzy targets, is investigated. Fuzzy targets are adopted to reflect human viewpoints on fuzzy ranking. Two important measures in DST, i.e., the belief and plausibility measures, are used to rank FSs. The proposed approach is evaluated with several benchmark examples. The use of the belief and plausibility measures in fuzzy ranking are discussed and compared. We further analyze the capability of the proposed approach in fulfilling six reasonable fuzzy ordering properties as discussed in [9]-[11]
In this paper, a new fuzzy ranking method for both type-1 and interval type-2 fuzzy sets (FSs) using...
AbstractDue to its wide practical use, data envelopment analysis (DEA) has been adapted to many fiel...
The problems of ranking fuzzy alternatives can be very complex and yet they are encountered in almos...
In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets a...
In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets a...
Fuzzy ranking is a procedure used to compare and order a sequence of fuzzy sets (FSs). It is an esse...
AbstractVarious approaches have been proposed for the comparison or ranking of fuzzy sets. However, ...
[[abstract]]The aim of this paper is to explore the belief feature in ranking fuzzy algorithm, becau...
This research aims to combine the mathematical theory of evidence with the rule based logics to refi...
Outranking methods are a family of techniques concerned with ranking the preference for alternatives...
AbstractThis paper proposes a new ranking method for fuzzy numbers, which uses a defuzzification of ...
Belief and plausibility measures in Dempster–Shafer theory (DST) and fuzzy sets are known as differe...
Part 7: DecisionsInternational audienceIn this study, we discuss the use of Dempster-Shafer theory a...
AbstractIntelligent systems often need to deal with various kinds of uncertain information. It is th...
This paper presents a discriminative analysis of approaches to ranking fuzzy numbers in fuzzy decisi...
In this paper, a new fuzzy ranking method for both type-1 and interval type-2 fuzzy sets (FSs) using...
AbstractDue to its wide practical use, data envelopment analysis (DEA) has been adapted to many fiel...
The problems of ranking fuzzy alternatives can be very complex and yet they are encountered in almos...
In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets a...
In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets a...
Fuzzy ranking is a procedure used to compare and order a sequence of fuzzy sets (FSs). It is an esse...
AbstractVarious approaches have been proposed for the comparison or ranking of fuzzy sets. However, ...
[[abstract]]The aim of this paper is to explore the belief feature in ranking fuzzy algorithm, becau...
This research aims to combine the mathematical theory of evidence with the rule based logics to refi...
Outranking methods are a family of techniques concerned with ranking the preference for alternatives...
AbstractThis paper proposes a new ranking method for fuzzy numbers, which uses a defuzzification of ...
Belief and plausibility measures in Dempster–Shafer theory (DST) and fuzzy sets are known as differe...
Part 7: DecisionsInternational audienceIn this study, we discuss the use of Dempster-Shafer theory a...
AbstractIntelligent systems often need to deal with various kinds of uncertain information. It is th...
This paper presents a discriminative analysis of approaches to ranking fuzzy numbers in fuzzy decisi...
In this paper, a new fuzzy ranking method for both type-1 and interval type-2 fuzzy sets (FSs) using...
AbstractDue to its wide practical use, data envelopment analysis (DEA) has been adapted to many fiel...
The problems of ranking fuzzy alternatives can be very complex and yet they are encountered in almos...