Book ChapterDOI
Fuzzy Soft Set Theory and Its Application in Group Decision Making
T. R. Sooraj,R. K. Mohanty,B. K. Tripathy +2 more
- pp 171-178
TLDR
A new algorithm is proposed by following this approach which provides an application of FSSs in group decision making and the performance is substantially improved than that of the earlier algorithm.Abstract:
Soft set theory was introduced by Molodtsov to handle uncertainty. It uses a family of subsets associated with each parameter. Hybrid models have been found to be more useful than the individual components. Earlier fuzzy set and soft set were combined to form fuzzy soft sets (FSS). Soft sets were defined from a different point of view in Tripathy et al. (Int J Reasoning-Based Intell Syst 7(3/4), 224–253, 2015) where they used the notion of characteristic functions. Hence, many related concepts were also redefined. In Tripathy et al. (Proceedings of ICCIDM-2015, 2015) membership function for FSSs was defined. We propose a new algorithm by following this approach which provides an application of FSSs in group decision making. The performance of this algorithm is substantially improved than that of the earlier algorithm.read more
Citations
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Book ChapterDOI
A New Approach to Interval-Valued Fuzzy Soft Sets and Its Application in Decision-Making
TL;DR: IVFSS is defined through the membership function approach to define soft set by Tripathy et al. very recently, and several concepts, such as complement of an IVFSS, null IVF SS, absolute IVFFS, intersection, and union of two IVFsss, are redefined.
Journal ArticleDOI
A novel algorithm for segmentation of leukocytes in peripheral blood
Haichao Cao,Hong Liu,Enmin Song +2 more
TL;DR: A fast and accurate algorithm for the segmentation of peripheral blood leukocytes is proposed that outperforms the existing non-fuzzy sets methods and performs slightly better than interval-valued intuitionistic fuzzy sets and intuitionistically fuzzy sets.
Proceedings ArticleDOI
On intuitionistic fuzzy soft set and its application in group decision making
TL;DR: This paper improves the group decision algorithm proposed by Tripathy et al earlier and provides an application in handling the decision making problem.
Journal ArticleDOI
(2,1)-Fuzzy sets: properties, weighted aggregated operators and their applications to multi-criteria decision-making methods
TL;DR: In this paper , a new class of orthopair fuzzy sets called (2,1)-Fuzzy sets are introduced, which are good enough to control some real-life situations.
Journal ArticleDOI
SR-Fuzzy Sets and Their Weighted Aggregated Operators in Application to Decision-Making
TL;DR: This manuscript familiarizes a new type of extensions of fuzzy sets called square-root fuzzy sets (briefly, SR-Fuzzy sets), and discovers the essential set of operations for the SR-Korean fuzzy sets along with their several properties.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI
Soft set theory—First results
TL;DR: The main purpose of this paper is to introduce the basic notions of the theory of soft sets, to present the first results of the the theory, and to discuss some problems of the future.
Journal ArticleDOI
Soft set theory
TL;DR: The authors define equality of two soft sets, subset and super set of a soft set, complement of asoft set, null soft set and absolute soft set with examples and De Morgan's laws and a number of results are verified in soft set theory.
Journal ArticleDOI
An application of soft sets in a decision making problem
TL;DR: In this article, the theory of soft sets was applied to solve a decision-making problem using rough mathematics, and the results showed that soft sets can be used to solve decision making problems.