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Review
Computer Science, Information Systems
Nancy Kumari et al.
Summary: Digitization is important in improving people's physical health, and healthcare organizations are focusing on precise disease diagnosis and patient care to enhance living standards. However, the vast amount of data generated through digitization contains uncertainties and impreciseness, requiring the application of computational intelligence techniques for analysis and processing.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Orhan Dalkilic et al.
Summary: Coronavirus disease (Covid-19) is a global public health problem caused by SARS-COV2. Its symptoms include fever, cough, and shortness of breath, although asymptomatic cases have also been reported. Severe cases can result in pneumonia, respiratory failure, kidney failure, and death. The study suggests considering different symptoms in various regions and using algorithms to analyze and evaluate the epidemic for better management.
Article
Biochemical Research Methods
Jia-Bao Liu et al.
Summary: This paper presents a novel hybrid model called m-polar Diophantine fuzzy N-soft set and defines its operations. The model proves to be more efficient and adaptable in managing uncertainties, overcoming the drawbacks of existing models. It generalizes several concepts and introduces the concept of m-polar Diophantine fuzzy N-soft sets.
COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING
(2022)
Article
Computer Science, Artificial Intelligence
Pengfei Zhang et al.
Summary: The paper introduces an Adaptive Multi-Granulation Decision-Theoretic Rough Sets (AMG-DTRS) model, which adaptively obtains probabilistic thresholds by setting a compensation coefficient. Three types of mean AMG-DTRS models are studied, offering a new perspective on information fusion. The advantages and generalization of the AMG-DTRS model are demonstrated by analyzing its connections and differences with existing MGRS models.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2022)
Article
Automation & Control Systems
Jose Carlos R. Alcantud
Summary: This paper aims to develop both soft topology and fuzzy soft topology by analyzing their mutual relationships. The construction and conclusions introduced in this paper provide new approaches for studying and applying these concepts in different settings.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
D. P. Acharjya et al.
Summary: Healthcare informatics data is challenging to analyze due to its complexity. This paper proposes an integration of rough set and bat algorithm to generate optimal decision rules and aid in the early diagnosis of diseases, providing an alternative opinion to physicians. The model shows promising results in preventing and detecting various diseases.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Multidisciplinary Sciences
Radwan Abu-Gdairi et al.
Summary: The rough set principle is an efficient method for dealing with the uncertainty of data in information systems. This paper introduces new topological approaches as a generalization of Pawlak's theory, elucidating the relationships between different types of approximations through examples. By comparing these approaches with previous ones, a more affirmative solution for decision-making problems can be obtained.
Article
Computer Science, Artificial Intelligence
Muhammad Akram et al.
Summary: This paper proposes a complex Fermatean fuzzy N-soft set algorithm and demonstrates its feasibility and effectiveness in multi-attribute decision making through various algorithms. It outperforms existing models and TOPSIS approaches.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2022)
Article
Mathematics, Applied
Ashraf S. Nawar et al.
Summary: The main objective of this work is to enhance the application aspects of Pawlak rough sets. Different methods for generalizing Pawlak rough sets are proposed and compared, along with new generalizations of Pawlak's models. The importance of decision-making methods is demonstrated through an application to real-life problems.
Article
Computer Science, Software Engineering
Nancy Kumari et al.
Summary: This paper introduces a decision support system that integrates rough set and artificial fish swarm optimization to handle uncertainties in healthcare data analysis. By applying the proposed model to hepatitis B disease, the results show that it achieves a high accuracy and outperforms other classical models.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Yiyu Yao et al.
Summary: This paper introduces the concept of Pawlak approximation space, explores the impact of the two-space view on rough set theory, proposes the notions of granular rough sets and probabilistic granular rough sets in the quotient space, and discusses the construction method and properties of granular shadowed sets.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2022)
Article
Computer Science, Artificial Intelligence
Mostafa K. El-Bably et al.
Summary: This article proposes three new methods for generalizing Pawlak rough sets based on topological structures, and proves that these methods are more accurate than other methods. Furthermore, a practical example in economic decision-making is used to demonstrate the application of these methods.
Article
Computer Science, Information Systems
Jose Carlos R. Alcantud et al.
Summary: This paper investigates the imprecision in information and knowledge, highlighting the role of convexity in the advancement of rough set theory. By introducing convex geometries and defining convex geometry approximation spaces, the authors establish connections between the proposed model and existing models in the field. They also classify subsets of the grand set according to their behavior with respect to cg-approximations and refine this classification in benchmark cases. Furthermore, a canonical convex geometry approximation space is generated from any covering on a set. The presented examples illustrate the constructions and main findings.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Jose Carlos R. Alcantud
Summary: This paper presents a detailed analysis of the semantics of N-soft sets for the first time. The two benchmark semantics associated with soft sets are a perfect fit for N-soft sets. N-soft sets allow for a new interpretation in logical terms, where they can be seen as a generalized form of incomplete soft sets. The study also introduces aggregation strategies and designs three-way decision models with qualitative and quantitative features.
INFORMATION SCIENCES
(2022)
Review
Mathematics, Applied
Orhan Dalkilic et al.
Summary: This paper discusses the application of bipolar soft rough sets in eliminating uncertainty and decision-making processes, introduces the concept of bipolar soft rough classes, and proposes a more efficient decision-making algorithm. In addition, several novel concepts are presented and their properties are examined in detail.
COMPUTATIONAL & APPLIED MATHEMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Jose Carlos R. Alcantud et al.
Summary: This work improves the theoretical basis of N-soft sets and demonstrates their practical applications in a multiagent context. It presents a novel theory of aggregation of N-soft sets using OWA operators and applies it to multi-agent decision-making, resulting in the first algorithms for such decisions based on N-soft sets.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics, Applied
El-Sayed A. Abo-Tabl et al.
Summary: This study introduces the structure of rough topological space based on the reflexive relation and investigates the relationships between approximation operators, closure operators, and interior operators, as well as the relationship between topological space and rough sets induced by reflexive relations. Furthermore, a medical application for addressing the issue of dengue fever is presented.
Article
Computer Science, Artificial Intelligence
Hanchuan Lu et al.
Summary: The article introduces the concept of generalized picture fuzzy soft sets and explains their operations, establishing several theoretical operations. The applicability of generalized picture fuzzy soft sets in fuzzy decision-making is demonstrated with a numerical example, and a comparison is made with picture fuzzy soft set theory.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Mathematics
Mostafa K. El-Bably et al.
Summary: This study focuses on addressing vagueness and ambiguity through soft rough sets and topological soft rough sets. The research answers important questions about the probability of defining subsets and enhances existing techniques. The proposed technique has shown improvement in accuracy and has been applied to diagnosing heart failure in decision-making problems.
JOURNAL OF MATHEMATICS
(2021)
Article
Physics, Multidisciplinary
Fairouz Tchier et al.
Summary: A novel hybrid model called picture fuzzy soft expert sets is proposed in this study by combining picture fuzzy sets with soft expert sets, aiming to deal with uncertainties in different decision-making problems. The model can be viewed as a more generalized form of intuitionistic fuzzy soft expert sets, with some novel desirable properties.
Article
Mathematical & Computational Biology
Mostafa K. El-Bably et al.
Summary: The paper aims to create new rough set models by using different neighborhoods generated by a binary relation, proposing new approximations that extend Pawlak's rough sets and some generalizations, with significantly improved precision. It also provides comparisons between the proposed methods and previous ones, as well as a medical application on lung cancer disease and an algorithm tested on hypothetical data for comparison with current methods.
INTERNATIONAL JOURNAL OF BIOMATHEMATICS
(2021)
Article
Mathematics
Radwan Abu-Gdairi et al.
Summary: The paper introduces new rough set approximations using a multi-knowledge base, based on a new neighborhood called basic-neighborhood. These proposed methods are a generalization of Pawlak's rough sets and some of their extensions, proving their best accuracy. The main goal is to study multi-information systems and extend the application field of rough set models, with discussions on real-life applications like nutrition modeling and decision-making in the medical field.
Article
Mathematics, Applied
M. El Sayed et al.
Summary: The research aims to propose a new neighborhood and generalization to expand the application fields of rough sets theory.
Article
Mathematics
Mostafa K. El-Bably et al.
Summary: Soft rough set theory is utilized as a mathematical model for decision-making with real-life data, with this article introducing modifications and generalizations for soft 0-rough approximations. The study includes comparisons with previous approaches and examples demonstrating the validity of the proposals, particularly in predicting COVID-19 infections.
TURKISH JOURNAL OF MATHEMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Jilin Yang et al.
KNOWLEDGE-BASED SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Jose Carlos R. Alcantud et al.
Article
Computer Science, Information Systems
Mingliang Suo et al.
INFORMATION SCIENCES
(2020)
Article
Mathematical & Computational Biology
M. El Sayed et al.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2020)
Article
Computer Science, Information Systems
Muhammad Gulzar et al.
Article
Computer Science, Artificial Intelligence
Jose Carlos R. Alcantud et al.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2020)
Review
Automation & Control Systems
D. P. Acharjya et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2020)
Article
Computer Science, Information Systems
Zhicai Liu et al.
Article
Health Care Sciences & Services
Kauser P. Ahmed et al.
JOURNAL OF MEDICAL SYSTEMS
(2019)
Article
Mathematical & Computational Biology
M. M. El-Sharkasy
INTERNATIONAL JOURNAL OF BIOMATHEMATICS
(2018)
Article
Computer Science, Artificial Intelligence
M. E. Abd El-Monsef et al.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2017)
Article
Computer Science, Artificial Intelligence
Jose Carlos R. Alcantud
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2016)
Article
Computer Science, Artificial Intelligence
Huili Dou et al.
KNOWLEDGE-BASED SYSTEMS
(2016)
Article
Computer Science, Artificial Intelligence
Muhammad Shabir et al.
KNOWLEDGE-BASED SYSTEMS
(2013)
Article
Mathematics, Applied
Zhaowen Li et al.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2012)
Article
Computer Science, Artificial Intelligence
Muhammad Irfan Ali
APPLIED SOFT COMPUTING
(2011)
Article
Computer Science, Information Systems
E. A. Abo-Tabl
INFORMATION SCIENCES
(2011)
Article
Computer Science, Information Systems
Feng Feng et al.
INFORMATION SCIENCES
(2011)
Article
Computer Science, Information Systems
Yiyu Yao
INFORMATION SCIENCES
(2010)
Article
Mathematics, Applied
A. R. Roy et al.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2007)
Article
Mathematics, Applied
PK Maji et al.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2002)
