scholarly journals New Soft Rough Set Approximations

2021 ◽  
Vol 21 (2) ◽  
pp. 123-134
Author(s):  
Shawkat Alkhazaleh ◽  
Emad A. Marei
Keyword(s):  
Rough Set ◽  
Soft Rough Set

scholarly journals On Soft Rough Topology with Multi-Attribute Group Decision Making

Mathematics ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 67 ◽  
Author(s):  
Muhammad Riaz ◽  
Florentin Smarandache ◽  
Atiqa Firdous ◽  
Atiqa Fakhar
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Group Decision Making ◽  
Topological Structure ◽  
Group Decision ◽  
Continuous Mapping ◽  
Product Topology ◽  
Closed Sets ◽  
Open Set ◽  
Soft Rough Set

Rough set approaches encounter uncertainty by means of boundary regions instead of membership values. In this paper, we develop the topological structure on soft rough set ( SR -set) by using pairwise SR -approximations. We define SR -open set, SR -closed sets, SR -closure, SR -interior, SR -neighborhood, SR -bases, product topology on SR -sets, continuous mapping, and compactness in soft rough topological space ( SRTS ). The developments of the theory on SR -set and SR -topology exhibit not only an important theoretical value but also represent significant applications of SR -sets. We applied an algorithm based on SR -set to multi-attribute group decision making (MAGDM) to deal with uncertainty.

scholarly journals Soft -Rough Set and Its Applications in Decision Making of Coronavirus

2022 ◽  
Vol 70 (1) ◽  
pp. 267-285
Author(s):  
M. A. El Safty ◽  
Samirah Al Zahrani ◽  
M. K. El-Bably ◽  
M. El Sayed
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Soft Rough Set

scholarly journals Intuitionistic Fuzzy Soft Rough Set and Its Application in Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Haidong Zhang ◽  
Lan Shu ◽  
Shilong Liao
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Intuitionistic Fuzzy Sets ◽  
Mathematical Tool ◽  
Intuitionistic Fuzzy ◽  
Rough Approximation ◽  
Soft Rough Set

The soft set theory, originally proposed by Molodtsov, can be used as a general mathematical tool for dealing with uncertainty. In this paper, we present concepts of soft rough intuitionistic fuzzy sets and intuitionistic fuzzy soft rough sets, and investigate some properties of soft rough intuitionistic fuzzy sets and intuitionistic fuzzy soft rough sets in detail. Furthermore, classical representations of intuitionistic fuzzy soft rough approximation operators are presented. Finally, we develop an approach to intuitionistic fuzzy soft rough sets based on decision making and a numerical example is provided to illustrate the developed approach.

Soft Rough Set based span for unsupervised keyword extraction

2021 ◽  
pp. 1-8
Author(s):  
Niladri Chatterjee ◽  
Aayush Singha Roy ◽  
Nidhika Yadav
Keyword(s):  
Greedy Algorithm ◽  
Rough Set ◽  
Rough Sets ◽  
Text Summarization ◽  
The Other ◽  
Keyword Extraction ◽  
Effective Solution ◽  
Input Text ◽  
Soft Rough Set ◽  
The Universe

The present work proposes an application of Soft Rough Set and its span for unsupervised keyword extraction. In recent times Soft Rough Sets are being applied in various domains, though none of its applications are in the area of keyword extraction. On the other hand, the concept of Rough Set based span has been developed for improved efficiency in the domain of extractive text summarization. In this work we amalgamate these two techniques, called Soft Rough Set based Span (SRS), to provide an effective solution for keyword extraction from texts. The universe for Soft Rough Set is taken to be a collection of words from the input texts. SRS provides an ideal platform for identifying the set of keywords from the input text which cannot always be defined clearly and unambiguously. The proposed technique uses greedy algorithm for computing spanning sets. The experimental results suggest that extraction of keywords using the proposed scheme gives consistent results across different domains. Also, it has been found to be more efficient in comparison with several existing unsupervised techniques.

scholarly journals A Novel Approach to Neutrosophic Soft Rough Set under Uncertainty

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 384 ◽  
Author(s):  
Ashraf Al-Quran ◽  
Nasruddin Hassan ◽  
Emad Marei
Keyword(s):  
Rough Set ◽  
Incomplete Data ◽  
Soft Set ◽  
Mathematical Tool ◽  
Soft Sets ◽  
Novel Approach ◽  
Proposed Model ◽  
Neutrosophic Logic ◽  
Soft Rough Set ◽  
Lower And Upper Approximations

To handle indeterminate and incomplete data, neutrosophic logic/set/probability were established. The neutrosophic truth, falsehood and indeterminacy components exhibit symmetry as the truth and the falsehood look the same and behave in a symmetrical way with respect to the indeterminacy component which serves as a line of the symmetry. Soft set is a generic mathematical tool for dealing with uncertainty. Rough set is a new mathematical tool for dealing with vague, imprecise, inconsistent and uncertain knowledge in information systems. This paper introduces a new rough set model based on neutrosophic soft set to exploit simultaneously the advantages of rough sets and neutrosophic soft sets in order to handle all types of uncertainty in data. The idea of neutrosophic right neighborhood is utilised to define the concepts of neutrosophic soft rough (NSR) lower and upper approximations. Properties of suggested approximations are proposed and subsequently proven. Some of the NSR set concepts such as NSR-definability, NSR-relations and NSR-membership functions are suggested and illustrated with examples. Further, we demonstrate the feasibility of the newly rough set model with decision making problems involving neutrosophic soft set. Finally, a discussion on the features and limitations of the proposed model is provided.

An approach to multiple attribute decision making based on linguistic value soft rough set and VIKOR method

2021 ◽  
pp. 1-18
Author(s):  
Xiangtang Chen ◽  
Bingzhen Sun ◽  
Xinrui Zhang ◽  
Chang Qi ◽  
Xiaoli Chu ◽  
...  
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Fuzzy Set ◽  
Multiple Attribute Decision Making ◽  
Soft Set ◽  
Linguistic Variable ◽  
Vikor Method ◽  
Multiple Attribute ◽  
Rough Approximation ◽  
Soft Rough Set

Linguistic variable is an effective method of representation the preferences of a decision-maker for inaccuracy available information in decision making under uncertainty. This article investigates a multiple attribute ranking decision making problem with linguistic preference by using linguistic value soft rough set. Firstly, we present the definition of linguistic value fuzzy set by introduce the concept of linguistic variable into the original Zadeh’s fuzzy set. We then define the concept of linguistic value soft set and the pseudo linguistic value soft set over the alternative set and parameter set of discourse. Moreover, we investigate the basic operators and the mathematical properties of the linguistic value soft set. Subsequently, we establish the rough approximation of an uncertainty concept with linguistic value over the object set and parameter set, i.e., the linguistic value soft rough set model. Meanwhile, we discuss several deformations of the linguistic value soft rough lower and upper approximations as well as some fundamental properties of the linguistic value soft approximation operators. With reference on the exploring of the fundamental of linguistic value soft rough set, we construct a new method for handling with the multiple attribute ranking decision making problems with linguistic information by combining the proposed soft rough set and the VIKOR method. Then, we give the detailed decision procedure and steps for the established decision approach. At last, an extensive numerical example is further conducted to illustrate the process of the decision making principle and the results are satisfactory. The main contribution of this paper is twofold. One is to provide a new model of granular computing by infusion the soft set and rough set theory with linguistic valued information. Another is to try making a new way to handle multiple attribute decision making problems based on linguistic value soft rough set and the VIKOR method.

A Lattice Structure on Minimal Soft Rough Sets and Its Applications

2020 ◽  
Vol 16 (02) ◽  
pp. 255-269
Author(s):  
B. Praba ◽  
G. Gomathi ◽  
M. Aparajitha
Keyword(s):  
Rough Set ◽  
Rough Sets ◽  
Culture System ◽  
Lattice Structure ◽  
Vital Role ◽  
Inclusion Relation ◽  
Soft Sets ◽  
Medical Diagnoses ◽  
Soft Rough Set ◽  
Made In

Rough sets defined in terms of soft sets play a vital role in decision making problems. Covering-based soft rough sets and modified soft rough sets are some of the recently developing concepts. In this paper, for a given soft sets [Formula: see text] on a universe [Formula: see text] we define a novel rough set called as minimal soft rough sets using minimal soft description of the objects. The relation between modified soft rough set and minimal soft rough set is analyzed. The set of all minimal soft rough sets is proved to be a Poset with the inclusion relation having a GLB and LUB and hence is a lattice. An attempt is made in applying this concepts in medical diagnoses and also in analyzing the organizational culture system.

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