Certain types of coverings based rough sets with application

Nawar, Ashraf S.; El-Bably, Mostafa K.; Atik, Abd El Fattah El

doi:10.3233/jifs-191542

Cited by 29 publications

(11 citation statements)

References 34 publications

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“…In covering-based rough sets, an adhesion-set is introduced [21]. Nawar et al [22] utilized it to define the j-adhesion neighbourhood formed by any binary relation, and they proposed different types of covering-based rough sets as a result. Furthermore, Atef et al [23] provided six rough approximations derived by j-adhesion neighbourhoods utilizing j-neighbourhood space [8] which was modified by El-Bably et al in [5].…”

Section: Introductionmentioning

confidence: 99%

“…Rough set theory was established by computer scientist Pawlak [24,25] based on several difficulties in computer science to overcome this challenge by a modal approximation of a crisp set in the expressions of a pair of sets called the rough approximations of it. Many writers have focused on generalization rough sets [2,4,8,11,13,20,22,23,[26][27][28][29][30][31][32][33][34][35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

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Topological Models of Rough Sets and Decision Making of COVID-19

El-Gayar

Atik

2022

Complexity

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The basic methodology of rough set theory depends on an equivalence relation induced from the generated partition by the classification of objects. However, the requirements of the equivalence relation restrict the field of applications of this philosophy. To begin, we describe two kinds of closure operators that are based on right and left adhesion neighbourhoods by any binary relation. Furthermore, we illustrate that the suggested techniques are an extension of previous methods that are already available in the literature. As a result of these topological techniques, we propose extended rough sets as an extension of Pawlak’s models. We offer a novel topological strategy for making a topological reduction of an information system for COVID-19 based on these techniques. We provide this medical application to highlight the importance of the offered methodologies in the decision-making process to discover the important component for coronavirus (COVID-19) infection. Furthermore, the findings obtained are congruent with those of the World Health Organization. Finally, we create an algorithm to implement the recommended ways in decision-making.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Topological Models of Rough Sets and Decision Making of COVID-19

El-Gayar

Atik

2022

Complexity

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“…Using soft β -rough approximations and soft rough topologies, which are generated by soft β -rough approximations, we make a topological reduction for the information system and then we identify the impact factors for transmission of COVID-19 infection into the human. Moreover, we can say that the suggested methods can be used to analyze data of COVID-19 with quantitative or qualitative data [35,36]. By coding qualitative data of the information system in the application, we express "yes" and "no" with " 1 " and " 0 " values, respectively, and obtain soft β -rough sets.…”

Section: Introductionmentioning

confidence: 99%

Softβ-rough sets and their application to determine COVID-19

El-Bably¹,

Atik²

2021

Turk J Math

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Soft rough set theory has been presented as a basic mathematical model for decision-making for many real-life data. However, soft rough sets are based on a possible fusion of rough sets and soft sets which were proposed by Feng et al. [20]. The main contribution of the present article is to introduce a modification and generalization for Feng's approximations, namely, soft β-rough approximations, and some of their properties will be studied. A comparison between the suggested approximations and the previous one [20] will be discussed. Some examples are prepared to display the validness of these proposals. Finally, we put an actual example of the infections of coronavirus (COVID-19) based on soft β-rough sets. This application aims to know the persons most likely to be infected with COVID-19 via soft β-rough approximations and soft β-rough topologies.

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“…erefore application of this technique is very limited. erefore authors relaxed the condition of equivalence relation by some more general relations such as similarity relations (reflexive and symmetric) [5,6], preorder relations (reflexive and transitive) [7], reflexive relations [8], general binary relations [8][9][10][11][12][13][14], topological approaches [15,16], and coverings [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

New Topological Approaches to Generalized Soft Rough Approximations with Medical Applications

El-Bably

Ali

Abo-Tabl

2021

Journal of Mathematics

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There are many approaches to deal with vagueness and ambiguity including soft sets and rough sets. Feng et al. initiated the concept of possible hybridization of soft sets and rough sets. They introduced the concept of soft rough sets, in which parameterized subsets of a universe set serve as the building blocks for lower and upper approximations of a subset. Topological notions play a vital role in rough sets and soft rough sets. So, the basic objectives of the current work are as follows: first, we find answers to some very important questions, such as how to determine the probability that a subset of the universe is definable. Some more similar questions are answered in rough sets and their extensions. Secondly, we enhance soft rough sets from topological perspective and introduce topological soft rough sets. We explore some of their properties to improve existing techniques. A comparison has been made with some existing studies to show that accuracy measure of proposed technique shows an improvement. Proposed technique has been employed in decision-making problem for diagnosing heart failure. For this two algorithms have been given.

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Certain types of coverings based rough sets with application

Cited by 29 publications

References 34 publications

Topological Models of Rough Sets and Decision Making of COVID-19

Topological Models of Rough Sets and Decision Making of COVID-19

Softβ-rough sets and their application to determine COVID-19

New Topological Approaches to Generalized Soft Rough Approximations with Medical Applications

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