Decision Making Based on Fuzzy Soft Sets and Its Application in COVID-19

Alblowi, S. A.; Sayed, M. El; Safty, M. A. El

doi:10.32604/iasc.2021.018242

Cited by 12 publications

(4 citation statements)

References 29 publications

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“…Some researchers have extended Pawlak's idea by incorporating fuzzy equivalence relations, neighborhood relations and dominance relations into Pawlak rough sets to form neighborhood rough sets [3,4], fuzzy rough sets [5][6][7][8][9], and dominance-based rough sets [10][11][12]. The generalized models of rough set are commonly applied in the reduction of attributes [13][14][15], feature selection [16][17][18][19], extraction of rules [20][21][22][23], theory of decisions [24][25][26], incremental learning [27][28][29],…”

Section: Introductionmentioning

confidence: 99%

Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

Eid¹,

Medhat²,

Ali³

2023

Computer Systems Science and Engineering

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An information system is a type of knowledge representation, and attribute reduction is crucial in big data, machine learning, data mining, and intelligent systems. There are several ways for solving attribute reduction problems, but they all require a common categorization. The selection of features in most scientific studies is a challenge for the researcher. When working with huge datasets, selecting all available attributes is not an option because it frequently complicates the study and decreases performance. On the other side, neglecting some attributes might jeopardize data accuracy. In this case, rough set theory provides a useful approach for identifying superfluous attributes that may be ignored without sacrificing any significant information; nonetheless, investigating all available combinations of attributes will result in some problems. Furthermore, because attribute reduction is primarily a mathematical issue, technical progress in reduction is dependent on the advancement of mathematical models. Because the focus of this study is on the mathematical side of attribute reduction, we propose some methods to make a reduction for information systems according to classical rough set theory, the strength of rules and similarity matrix, we applied our proposed methods to several examples and calculate the reduction for each case. These methods expand the options of attribute reductions for researchers.

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Section: Introductionmentioning

confidence: 99%

Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

Eid¹,

Medhat²,

Ali³

2023

Computer Systems Science and Engineering

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“…These studies highlight the potential of nano topology in medical decision-making, paving the way for improved diagnostic capabilities and patient outcomes. Abd El Monsef et al [6] introduced the notion of 𝛽-open set in Topology, and its practical implications, have been central topics in various realworld applications (such as [7,8], [15][16][17]). In (2013), Thivagar et al [ [1], [9]] Introduced the notion of a "nano-topology" derived from a generalized topology generated by Pawlak's rough set approximations.…”

Section: Introductionmentioning

confidence: 99%

Topological Approach with Decision Making Based on Nano Beta Closure, Nano Beta Interior and its Application with Fractals in Medical Fields

El Safty,

El Sayed,

Al-Qahtani

et al. 2023

Preprint

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In this paper we introduce the concept of Nano Beta Closure, Nano Beta Interior and study the relationship between them also study some of their properties. Based on these notions we introduced the topological Approach to Decision Making and Its Application in the Medical Field" which describes the use of topological methods in decision-making, specifically through the utilization of nano beta closure and nano beta interior. These mathematical tools are applied in the medical field to improve diagnostic accuracy and aid in treatment planning. The authors demonstrate the effectiveness of this approach through a case study on the diagnosis of Chronic Kidney. The results show that the topological approach using nano beta closure and nano beta interior provides a reliable and accurate method for medical decision-making. Finally, we introduce a medical application for disease groups patients of with chronic kidney. To identify the main causative agent of kidney disease. where using this approach, the medical team can identify the specific areas of the kidney that are affected by the infection, as well as the extent of damage and any potential complications. This information is used to create an individualized treatment strategy that is customized to meet the specific requirements of the patient. and medical history. We write an algorithm that can be a helpful tool for doctors to utilize in diagnosing infection disease Chronic Kidney infections. By utilizing this approach, clinicians can provide accurate diagnoses, develop effective treatment plans, and ultimately improve patient outcomes. finally, we show that fractals hold significant importance in future nano topological generation of the human factor. Their unique properties and self-similar patterns offer insights into the complex organization of biological systems and provide a foundation for designing advanced Nanosystems.

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“…They have always been very close to each other. Authors the first fuzzy set theory papers, like [17][18][19][20] show that they wanted to change the way people think about things, like how they judge, evaluate, and make decisions.…”

Section: Introductionmentioning

confidence: 99%

Rough fuzzy-topological approximation space with tooth decay in decision making

Alzahrani

2022

THERM SCI

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Tooth decay is a common problem among people due to many factors, including neglect to clean teeth. Dental caries is becoming more common in a number of countries worldwide. This study aims to determine the prevalence of dental caries and how to treat this problem. We also implement fuzzy soft multifunction between fuzzy soft topological spaces which is Smarandache?s generation of the notion. In this paper, we generated additional topologies for an information system based on a similarity relation. This paper discussed two methods for determining accuracy: our method and Pawlak?s qualitative data method. Both ideas show that because of the uncertainty and ambiguity of qualitative data, we get a lot of topologies based on one or two attributes. The new method was used to determine the accuracies. This method revealed the difference between one or two attributes. In fact, the most important factors affecting tooth decay have been identified. Furthermore, we are developing a new algorithm to treat dental caries problems. Tooth decay which includes the conclusions of some well-known results in the corresponding literature is highlighted and discussed. In addition, a comparative application that dwells on the generality of our obtained results is constructed. Our proposed approach is reasonable and effective.

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Decision Making Based on Fuzzy Soft Sets and Its Application in COVID-19

Cited by 12 publications

References 29 publications

Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

Topological Approach with Decision Making Based on Nano Beta Closure, Nano Beta Interior and its Application with Fractals in Medical Fields

Rough fuzzy-topological approximation space with tooth decay in decision making

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