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Open AccessJournal ArticleDOI

Soft set theory—First results

TLDR
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.
Abstract
The soft set theory offers a general mathematical tool for dealing with uncertain, fuzzy, not clearly defined objects. 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 theory, and to discuss some problems of the future.

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Citations
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Journal ArticleDOI

A Framework for Medical Images Classification Using Soft Set

TL;DR: A new framework for medical imaging classification consisting of six phases namely: data acquisition, data pre-processing, data partition, soft set classifier, data analysis and performance evolution is presented and it is expected that soft setclassifier will provide better results in terms of sensitivity, specificity, running time and overall classifier accuracy.
Journal ArticleDOI

An introduction to fuzzy soft topological spaces

TL;DR: The aim of this study is to dene fuzzy soft topology which will be compatible to the fuzzy soft theory and investigate some of its fundamental properties.
Journal ArticleDOI

Soft Open Bases and a Novel Construction of Soft Topologies from Bases for Topologies

TL;DR: A general construction of soft topologies from topologies on the set of alternatives in two different directions is extended and the first non-trivial examples of soft second-countable soft topological spaces are produced as a consequence.
Journal ArticleDOI

Systematic review of decision making algorithms in extended neutrosophic sets

TL;DR: This paper contains an extended overview of the concept of NS as well as several instances and extensions of this model that have been introduced in the last decade, and have had a significant impact in literature.

Special Issue: Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets, Vol. II

TL;DR: The aim of this paper is to introduce some new operators for aggregating single-valued neutrosophic (SVN) information and to apply them to solve the multi-criteria decision-making (MCDM) problems.
References
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