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We then define fuzzy soft aggregation operator that allows con- structing more efficient decision making method. Finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties. 1. Introduction. Molodtsov [23] introduced the concept of soft sets that can be
Finally we define arbitrary fuzzy soft union and fuzzy soft intersection and prove DeMorgan Inclusions and DeMorgan Laws in Fuzzy Soft Set Theory. . Full text: PDF. Additional sources: Publisher Site. Several properties of fuzzy semiclosure and fuzzy semi-interior of fuzzy sets defined by Yalvac (1988), have been
Jun 5, 2009 Recommended by Yasar Becerikli. We further contribute to the properties of fuzzy soft sets as defined and studied in the work of Maji et al. ( 2001), Roy and Maji. (2007), and Yang et al. (2007) and support them with examples and counterexamples. We improve Proposition 3.3 by Maji et al.,. (2001) . Finally
Abstract—In this paper, three new operations are introduced on intuitionistic fuzzy soft sets .They are based on concentration, dilatation and normalization of intuitionistic fuzzy sets. Some examples of these operations were given and a few important properties were also studied. Index Terms—Soft Set, Intuitionistic Fuzzy
Oct 27, 2017 Abstract: Zadeh's fuzzy set theory for imprecise or vague data has been followed by other successful models, inclusive of Molodtsov's soft set theory and hybrid models like fuzzy soft sets. Their success has been backed up by applications to many branches like engineering, medicine, or finance.
Dec 20, 2017 Full-text (PDF) | We further contribute to the properties of fuzzy soft sets as defined and studied in the work of Maji et al. ( 2001), Roy and Maji (2007), and Yang et al. (2007) and support them with examples and counterexamples. We improve Proposition 3.3 by Maji et al., (2001). Finally we defi
and Sut [8] have studied the notions of fuzzy soft union, fuzzy soft intersection, complement of a fuzzy soft set and several other properties of fuzzy soft sets along with examples and proofs of certain results. In this paper, we have studied some operations and results available in the literature of fuzzy soft sets. Instead of taking.
Fuzzy set was introduced by Zadeh in 1 as a mathematical way to represent and deal with vagueness in everyday life. After that many authors have studied the applications of fuzzy sets in different areas see Klir and Yuan 2 . Molodtsov 3 initiated the theory of soft sets as a new mathematical tool for dealing with uncertainties
1. Introduction. Molodtsov initiated the theory of soft sets as a new mathematical tool for dealing with uncertainties which traditional mathematical tools cannot handle. He has shown several applications of this theory in solving many practical problems in economics, engineering, social science, medical science, etc.
In this paper we define generalized intuitionistic fuzzy soft sets and set theoretical operations with illustrating examples. It also proposes a similarity measure for generalized intuitionistic fuzzy soft set and used it to find out the similarity between synthetic texture and natural texture. A congenial method for solving multi criteria

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March 2018