Modified rough bipolar soft sets

2020 ◽  
Vol 39 (3) ◽  
pp. 4259-4283
Author(s):  
Muhammad Shabir ◽  
Rizwan Gul
Keyword(s):  
Rough Set ◽  
Rough Sets ◽  
Group Decision ◽  
Soft Set ◽  
New Technique ◽  
Approximation Space ◽  
Soft Sets ◽  
Accuracy Measure ◽  
Soft Rough Set ◽  
A New Technique

Bipolar soft sets and rough sets are two different techniques to cope with uncertainty. A possible fusion of rough sets and bipolar soft sets is proposed by Karaaslan and Çağman. They introduced the notion of bipolar soft rough set. In this article, a new technique is being introduced to study roughness through bipolar soft sets. In this new technique of finding approximations of a set, flavour of both theories of bipolar soft set and rough set is retained. We call this new hybrid model modified rough bipolar soft set MRBS-set. Moreover, accuracy measure and roughness measure of modified rough bipolar soft sets are defined in MRBS-approximation space and its application in multi-criteria group decision making is presented.

scholarly journals Some More Results on IF Soft Rough Approximation Space

2011 ◽  
Vol 2011 ◽  
pp. 1-10
Author(s):  
Sharmistha Bhattacharya (Halder) ◽  
Bijan Davvaz
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Soft Set ◽  
Approximation Space ◽  
Rough Approximation ◽  
Frame Work ◽  
Set Approximation

Fuzzy sets, rough sets, and later on IF sets became useful mathematical tools for solving various decision making problems and data mining problems. Molodtsov introduced another concept soft set theory as a general frame work for reasoning about vague concepts. Since most of the data collected are either linguistic variable or consist of vague concepts so IF set and soft set help a lot in data mining problem. The aim of this paper is to introduce the concept of IF soft lower rough approximation and IF upper rough set approximation. Also, some properties of this set are studied, and also some problems of decision making are cited where this concept may help. Further research will be needed to apply this concept fully in the decision making and data mining problems.

scholarly journals Soft Rough Approximation Operators and Related Results

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Zhaowen Li ◽  
Bin Qin ◽  
Zhangyong Cai
Keyword(s):  
Topological Space ◽  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Soft Set ◽  
Soft Sets ◽  
Approximation Operators ◽  
Rough Approximation ◽  
Generalized Rough Set ◽  
Special Case

Soft set theory is a newly emerging tool to deal with uncertain problems. Based on soft sets, soft rough approximation operators are introduced, and soft rough sets are defined by using soft rough approximation operators. Soft rough sets, which could provide a better approximation than rough sets do, can be seen as a generalized rough set model. This paper is devoted to investigating soft rough approximation operations and relationships among soft sets, soft rough sets, and topologies. We consider four pairs of soft rough approximation operators and give their properties. Four sorts of soft rough sets are investigated, and their related properties are given. We show that Pawlak's rough set model can be viewed as a special case of soft rough sets, obtain the structure of soft rough sets, give the structure of topologies induced by a soft set, and reveal that every topological space on the initial universe is a soft approximating space.

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.

scholarly journals Soft Classes and Soft Rough Classes with Applications in Decision Making

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Faruk Karaaslan
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Rough Sets ◽  
Soft Set ◽  
Mathematical Tool ◽  
Soft Sets ◽  
Novel Method ◽  
Lower And Upper Approximations

Rough set was defined by Pawlak in 1982. Concept of soft set was proposed as a mathematical tool to cope with uncertainty and vagueness by Molodtsov in 1999. Soft sets were combined with rough sets by Feng et al. in 2011. Feng et al. investigated relationships between a subset of initial universe of soft set and a soft set. Feng et al. defined the upper and lower approximations of a subset of initial universe over a soft set. In this study, we firstly define concept of soft class and soft class operations such as union, intersection, and complement. Then we give some properties of soft class operations. Based on definition and operations of soft classes, we define lower and upper approximations of a soft set. Subsequently, we introduce concept of soft rough class and investigate some properties of soft rough classes. Moreover, we give a novel decision making method based on soft class and present an example related to novel 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.

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 An algorithm for fuzzy soft set based decision making approach

2020 ◽  
Vol 30 (1) ◽  
pp. 59-70
Author(s):  
Shehu Mohammed ◽  
Akbar Azam
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Soft Set ◽  
Mathematical Tool ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Fuzzy Soft Sets ◽  
Priority Table

The notion of soft set theory was initiated as a general mathematical tool for handling ambiguities. Decision making is viewed as a cognitive-based human activity for selecting the best alternative. In the present time, decision making techniques based on fuzzy soft sets have gained enormous attentions. On this development, this paper proposes a new algorithm for decision making in fuzzy soft set environment by hybridizing some existing techniques. The first novelty is the idea of absolute scores. The second concerns the concept of priority table in group decision making problems. The advantages of our approach herein are stronger power of objects discrimination and a well-determined inference.

scholarly journals Two Types of Intuitionistic Fuzzy Covering Rough Sets and an Application to Multiple Criteria Group Decision Making

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 462 ◽  
Author(s):  
Jingqian Wang ◽  
Xiaohong Zhang
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Group Decision Making ◽  
Rough Sets ◽  
Group Decision ◽  
Multiple Criteria ◽  
Approximation Spaces ◽  
Intuitionistic Fuzzy ◽  
Definition Of ◽  
Covering Rough Set

Intuitionistic fuzzy rough sets are constructed by combining intuitionistic fuzzy sets with rough sets. Recently, Huang et al. proposed the definition of an intuitionistic fuzzy (IF) β -covering and an IF covering rough set model. In this paper, some properties of IF β -covering approximation spaces and the IF covering rough set model are investigated further. Moreover, we present a novel methodology to the problem of multiple criteria group decision making. Firstly, some new notions and properties of IF β -covering approximation spaces are proposed. Secondly, we study the characterizations of Huang et al.’s IF covering rough set model and present a new IF covering rough set model for crisp sets in an IF environment. The relationships between these two IF covering rough set models and some other rough set models are investigated. Finally, based on the IF covering rough set model, Huang et al. also defined an optimistic multi-granulation IF rough set model. We present a novel method to multiple criteria group decision making problems under the optimistic multi-granulation IF rough set model.

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.

Sign in / Sign up

Export Citation Format

Share Document