Titlebook: Generalized Rough Sets; Hybrid Structure and Anjan Mukherjee Book 2015 Springer India 2015 Fuzzy Set Theory.IVIFS.IVIFS Closed Sets.IVIFS O

FRAX-tool

https://doi.org/10.1007/978-1-4684-3821-5hapter, the concept of generalised interval-valued intuitionistic fuzzy soft sets is introduced. The basic properties of these sets are presented. Also, an application of generalised interval-valued intuitionistic fuzzy soft sets in decision-making with respect to interval of degree of preference is investigated.

火海

On Generalised Interval-Valued Intuitionistic Fuzzy Soft Sets,hapter, the concept of generalised interval-valued intuitionistic fuzzy soft sets is introduced. The basic properties of these sets are presented. Also, an application of generalised interval-valued intuitionistic fuzzy soft sets in decision-making with respect to interval of degree of preference is investigated.

微不足道

Soft Rough Intuitionistic Fuzzy Sets,y sets. Feng et al. (Soft Compt 14:899–911, 2009 [.]) introduced lower and upper soft rough approximation of fuzzy sets in a soft approximation space and obtained a new hybrid model called soft rough fuzzy sets which is the extension of Dubois and Prade’s rough fuzzy sets. The aim of this chapter is

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Eructation

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训诫

https://doi.org/10.1007/978-1-4684-3821-5intuitionistic fuzzy sets into the theory of soft sets, Maji et al. proposed the concept of intuitionistic fuzzy soft set theory. The notion of the interval-valued intuitionistic fuzzy sets was first introduced by Atanassov and Gargov. It is characterised by an interval-valued membership degree and

两种语言

Karen Horney,Erich Fromm,Harry S. Sullivan, 1999 [.]) initiated a novel concept called soft sets, a new mathematical tool for dealing with uncertainties. It has been found that fuzzy sets, rough sets, and soft sets are closely related concepts (Aktas and Cagman in Inf Sci 1(77):2726–2735, 2007 [.]). Research works on soft sets are very acti

改良

https://doi.org/10.1007/978-1-349-16519-3gh set-based multi-criteria group decision-making scheme is presented, which refines the primary evaluation of the whole expert group and enables us to select the optimal object in a most reliable manner. The proposed scheme is illustrated by an example regarding the candidate selection problem.