Journal ArticleDOI
A survey of decision making methods based on certain hybrid soft set models
Xueling Ma,Qi Liu,Jianming Zhan +2 more
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TLDR
Some decision making methods based on (fuzzy) soft sets, rough soft sets and soft rough sets are reviewed, providing several novel algorithms in decision making problems by combining these kinds of hybrid models.Abstract:
Fuzzy set theory, rough set theory and soft set theory are all generic mathematical tools for dealing with uncertainties. There has been some progress concerning practical applications of these theories, especially, the use of these theories in decision making problems. In the present article, we review some decision making methods based on (fuzzy) soft sets, rough soft sets and soft rough sets. In particular, we provide several novel algorithms in decision making problems by combining these kinds of hybrid models. It may be served as a foundation for developing more complicated soft set models in decision making.read more
Citations
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A novel type of soft rough covering and its application to multicriteria group decision making
TL;DR: A novel type of soft rough covering is introduced by means of soft neighborhoods, and then it is used to improve decision making in a multicriteria group environment.
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N-soft sets and their decision making algorithms
TL;DR: This paperMotivated and introduced the concept of N-soft set as an extended soft set model, which is a cogent model for binary and non-binary evaluations in numerous kinds of decision making problems.
Journal ArticleDOI
A survey of decision making methods based on two classes of hybrid soft set models
TL;DR: By compromising the above three uncertain theories, some reviews to DM methods based on two classes of hybrid soft models: SRF-sets and SFR-sets are elaborate and an overview of techniques based on the involved hybrid soft set models is expatiate.
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A survey of parameter reduction of soft sets and corresponding algorithms
TL;DR: Some different algorithms of parameter reduction based on some types of (fuzzy) soft sets are reviewed to emphasize their respective advantages and disadvantages, and give some examples to illustrate their differences.
Journal ArticleDOI
Group decision-making methods based on hesitant N-soft sets
TL;DR: A new hybrid model called hesitant N- soft sets is introduced by a suitable combination of hesitancy with N-soft sets, a model that extends N-hard sets and investigates some useful properties and construct fundamental operations on them.
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
Rough sets
TL;DR: This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.
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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.
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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.