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Soft rough fuzzy sets and soft fuzzy rough sets

TLDR
A new soft rough set model is proposed and its properties are derived and a more general model called soft fuzzy rough set is established.
Abstract
Fuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing with uncertainties and are closely related. Feng et al. introduced the notions of rough soft set, soft rough set and soft rough fuzzy set by combining fuzzy set, rough set and soft set all together. This paper is devoted to the further discussion of the combinations of fuzzy set, rough set and soft set. A new soft rough set model is proposed and its properties are derived. Furthermore, fuzzy soft set is employed to granulate the universe of discourse and a more general model called soft fuzzy rough set is established. The lower and upper approximation operators are presented and their related properties are surveyed.

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Citations
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Journal ArticleDOI

Generalized picture distance measure and applications to picture fuzzy clustering

TL;DR: A generalized picture distance measure is proposed and integrated to a novel hierarchical picture fuzzy clustering method called Hierarchical Picture Clustering (HPC) and Experimental results show that the clustering quality of the proposed algorithm is better than those of the relevant ones.
Journal ArticleDOI

A survey of decision making methods based on certain hybrid soft set models

TL;DR: 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.
Journal ArticleDOI

On a novel uncertain soft set model

TL;DR: A kind of novel soft set model called a Z-soft fuzzy rough set is presented by means of three uncertain models: soft sets, rough sets and fuzzy sets, which is an important generalization of Z- soft rough fuzzy sets.
Journal ArticleDOI

A novel soft rough fuzzy set: Z-soft rough fuzzy ideals of hemirings and corresponding decision making

TL;DR: The notion of Z-soft rough fuzzy sets of hemirings is introduced, which is an extended notion of soft rough sets andrough fuzzy sets that removes the limiting condition that full soft sets require in Feng-soft rougher sets and Meng-soft Rough fuzzy sets.
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.
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.
Book

Rough Sets: Theoretical Aspects of Reasoning about Data

TL;DR: Theoretical Foundations.
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.
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

Rough fuzzy sets and fuzzy rough sets

TL;DR: It is argued that both notions of a rough set and a fuzzy set aim to different purposes, and it is more natural to try to combine the two models of uncertainty (vagueness and coarseness) rather than to have them compete on the same problems.
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