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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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A new approach in handling soft decision making problems

TL;DR: In inverse soft sets and inverse fuzzy soft sets are defined and used to solve decision making problems in a slightly modified way by using inverse (fuzzy) soft sets instead of (f fuzzy)soft sets which makes the algorithms easier and faster than the existed methods.
Journal ArticleDOI

Neutrosophic Left Almost Semigroup

TL;DR: In this paper, the theory of neutrosophy is extended to neutrosophic LA-semigroup and the ideal theory of LA-Semigroup is discussed and different kinds of ideal ideals are discussed.
Journal ArticleDOI

Caliber and Chain Conditions in Soft Topologies

TL;DR: This paper introduces two types of axioms that generalize suitable concepts of soft separability and explores the role of cardinality in their study, and the relationships among these and other properties.
Journal ArticleDOI

A new type of generalized picture fuzzy soft set and its application in decision making

TL;DR: A novel concept of the generalized picture fuzzy soft set is proposed by combining the picture fuzzySoft set and the fuzzy parameter set to provide decision makers a more mathematical insight before making decisions on their options.
Journal ArticleDOI

n-Valued Refined Neutrosophic Soft Sets and their Applications in Decision Making Problems and Medical Diagnosis

TL;DR: A similarity measure between two ‘n’-valued refined neutrosophic soft sets and its properties to solve decision making problems and a medical diagnosis method is established using similarity measures.
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