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Article
Computer Science, Artificial Intelligence
Tareq M. M. Al-shami et al.
Summary: We introduce a new type of neighborhood called subset neighborhood, defined under an arbitrary binary relation using the inclusion relations between N-rho-neighborhoods. We study its relationships with existing neighborhood systems and propose S-rho-lower and S-rho-upper approximations, as well as accuracy and roughness measures based on S-rho-neighborhoods. We compare our approach with existing ones and highlight the advantages in obtaining accuracy measures under specific relations. Two medical examples are provided to support the obtained results.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Mathematics, Interdisciplinary Applications
Tareq M. Al-shami et al.
Summary: This paper presents rough approximations based on topology, using 8 types of E-neighborhoods to construct approximations of any subset X of U, and studying properties and relationships between these approximations. It also provides some easy-to-understand examples and compares our approximations with those in published literature.
Article
Computer Science, Artificial Intelligence
Tareq M. Al-shami
Summary: The paper introduces the concept of somewhere dense sets to improve approximations in rough set theory, defining new concepts such as SD-lower and SD-upper approximations. It compares the new method with previous ones and shows that the current method is more accurate through examples.
Article
Computer Science, Information Systems
Tareq M. Al-shami
Summary: The rough set theory introduces new types of neighborhoods called containment neighborhoods and defines concepts of C-j-lower and C-j-upper approximations. The approach is successfully applied in a medical application aiming to classify medical staff in terms of suspected infection with COVID-19, showing the effectiveness of the technique.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Tareq M. Al-shami et al.
Summary: In 1982, Pawlak introduced the concept of rough sets as a new mathematical tool to address vagueness and uncertain knowledge. Some researchers have recently explored the application of topological concepts in rough set theory. This discussion further studies properties of N-j-neighborhoods and introduces new types of approximation spaces with established main properties. Comparisons are made between the approximations and accuracy measures in this study and those induced from topological operators and E-neighborhoods.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
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
Masooma Raza Hashmi et al.
Summary: Modeling uncertainties using SLDFS is a robust approach for various applications and can effectively handle limitations in existing models. By introducing reference parameters, strict restrictions on certain indexes can be removed, allowing for more flexibility. The concepts of SLDFNs and new algorithms enhance the analysis and management of uncertainties in MCDM.
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
Computer Science, Artificial Intelligence
Muhammad Riaz et al.
Summary: This paper introduces the concept of soft multi-rough set and defines soft multi-rough topology, suitable for modeling uncertainties and developing algorithms for multi-criteria decision making. The applications of SMRS and SMR-topology in diagnosing depression and diabetes are illustrated through numerical examples, and comparison analysis with existing methods is provided to justify their reliability, feasibility and flexibility.
Article
Multidisciplinary Sciences
Muhammad Riaz et al.
Article
Computer Science, Artificial Intelligence
A. S. Nawar et al.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Mohammed Atef et al.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2020)
Article
Mathematical & Computational Biology
Ashraf S. Nawar et al.
INTERNATIONAL JOURNAL OF BIOMATHEMATICS
(2019)
Article
Computer Science, Artificial Intelligence
Mona Hosny
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(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
W. S. Amer et al.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2017)
Article
Computer Science, Artificial Intelligence
Liwen Ma
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2012)
Article
Computer Science, Information Systems
Keyun Qin et al.
INFORMATION SCIENCES
(2008)
Article
Computer Science, Information Systems
William Zhu
INFORMATION SCIENCES
(2007)
Article
Mathematics
T Noiri et al.
ACTA MATHEMATICA HUNGARICA
(2004)