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Soft Sets and Soft Modules

2008
Molodtsov introduced the concept of soft sets.Recently, Aktas et al. generalized soft sets by defining the concept of soft groups. In this paper, we present the definition of soft modules and construct some basic properties using modules and Molodtsov's definition of soft sets.
Qiu-Mei Sun, Zi-Long Zhang, Jing Liu
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Probabilistic Soft Sets

2010 IEEE International Conference on Granular Computing, 2010
In this paper, we incorporate Molodtsov’s soft set theory with probability theory and then propose the notion of probabilistic soft sets. We provide some examples of probabilistic soft sets, which seem difficult to be described by the standard soft set and its variants in the literature.
Ping Zhu 0001, Qiaoyan Wen
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Comparison of the concepts of soft set, fuzzy soft set and L-fuzzy set

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011
This paper consists of two related but independent parts: (1) Characterizing separation axioms of topological spaces with soft sets. (2) Comparing the concepts of soft set, fuzzy soft set and L-fuzzy set.
Li Fu, Pingshu Wang
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Tolerance Soft Set Relation on a Soft Set and its Matrix Applications

Fundamenta Informaticae, 2017
In this paper the tolerance soft set relation on a soft set is defined and some examples are given with their matrix representations. Also, pre-class and tolerance class concepts for a given tolerance soft set relation are introduced and some examples related to these definitions are illustrated.
Polat, Nazan Çakmak   +2 more
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Hard and Soft Sets

1994
In this paper I would like to make some remarks on the concept of a set in the context of some recent developments concerning vagueness, imprecision and uncertainty.
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Probabilistic soft sets and dual probabilistic soft sets in decision-making

Neural Computing and Applications, 2017
Since its introduction by Molodstov (Computers & Mathematics with Applications 37(4):19–31 1999), soft set theory has been widely applied in various fields of study. Soft set theory has also been combined with other theories like fuzzy sets theory, rough sets theory, and probability theory.
Fatia Fatimah   +3 more
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Soft decision making methods based on fuzzy sets and soft sets

Journal of Intelligent & Fuzzy Systems, 2016
In this paper, we propose soft decision making methods based on fuzzy and soft set theory. We also use matrix representation of the soft sets that is very useful for computations of the method. We finally present an example which shows that the method can be successfully applied to many problems that contain uncertainties.
Haci Aktas, Naim Çagman
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An extended soft set model: Type-2 fuzzy soft sets

2011 IEEE International Conference on Cloud Computing and Intelligence Systems, 2011
The soft set theory has been initiated by Molodtsov as a useful mathematical tool for dealing with uncertainty, fuzzy, not clearly defined objects. However, it is inappropriate to be used to deal with fuzzy parameters that involve uncertain words, linguistic terms and have a non-measurable domain.
Xi'ao Ma, Guoyin Wang 0001
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Rough Soft Sets in Fuzzy Setting

2013
Fuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing with uncertainties and are closely related. In the paper, we define the notion of a soft set in L-set theory, introduce several operators for L-soft set theory, and investigate the rough operators on the set of all L-soft sets induced by the rough operators on L X
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Soft Sets

2014
This chapter is about soft sets. A brief account of the developments that took place in last 14 years in the field of Soft Sets Theory (SST) has been presented. It begins with a brief introduction on soft sets and then it describes many generalizations of it. The notions of generalized fuzzy soft sets are defined and their properties are studied. After
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