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Autonomous clustering using rough set theory [PDF]
International Journal of Automation and Computing, 2008 This paper proposes a clustering technique that minimises the need for subjective\ud human intervention and is based on elements of rough set theory. The proposed algorithm is\ud unified in its approach to clustering and makes use of both local and global data properties to\ud obtain clustering solutions. It handles single-type and mixed attribute data
Kambhampati, Chandra, Bean, Charlotte
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Rough set theory and its applications
Journal of Telecommunications and Information Technology, 2002 In this paper rudiments of the theory will be outlined, and basic concepts of the theory will be illustrated by a simple tutorial example, concerning churn modeling in telecommunications.
Zdzisław Pawlak
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Topology in the Alternative Set Theory and Rough Sets via Fuzzy Type Theory
Mathematics, 2020 In this paper, we will visit Rough Set Theory and the Alternative Set Theory (AST) and elaborate a few selected concepts of them using the means of higher-order fuzzy logic (this is usually called Fuzzy Type Theory).
Vilém Novák
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Sub-exact sequence of rough groups
Al-Jabar, 2021 Rough Set Theory (RST) is an essential mathematical tool to deal with imprecise, inconsistent, incomplete information and knowledge Rough Some algebra structures, such as groups, rings, and modules, have been presented on rough set theory.
Nevi Setyaningsih +2 more
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Computing fuzzy rough approximations in large scale information systems [PDF]
, 2014 Rough set theory is a popular and powerful machine learning tool. It is especially suitable for dealing with information systems that exhibit inconsistencies, i.e. objects that have the same values for the conditional attributes but a different value for
Asfoor, Hasan +7 more
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Topological Properties of Generalized Rough Approximation Operators Based on Objects [PDF]
Jisuanji kexue, 2023 Rough set theory is a mathematical tool to deal with uncertain problems.The core notion of rough set theory is appro-ximation operators.Pawlak approximation operators based on equivalence relations cab be extended to generalized rough approximation ...
LI Yanyan, QIN Keyun
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On Uncertainty Measure Issues in Rough Set Theory
IEEE Access, 2020 Rough set theory is a tool for dealing with uncertainty problems. How to measure the uncertainty of a knowledge is an important issue in the theory. However, the existing uncertainty measures may not accurately reflect the uncertainty degree.
Jianguo Tang +3 more
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An Attempt of Object Reduction in Rough Set Theory [PDF]
, 2019 Attribute reduction is a popular topic in rough set theory; however, object reduction is not considered popularly. In this paper, from a viewpoint of computing all relative reducts, we introduce a concept of object reduction that reduces the number of ...
KUDO Yasuo, MURAI Tetsuya
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SOME PROPERTIES OF INDUCED COVER FROM FAMILY OF COVERING ROUGH SETS
Tạp chí Khoa học Đại học Đà Lạt, 2017 Rough set theory is an efficient and essential tool for dealing with vagueness and granularity in information systems. Covering based rough set theory is proposed as a significant generalization of classical rough sets.
Nguyễn Đức Thuần
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River pattern discriminant method based on Rough Set theory
Journal of Hydrology: Regional Studies, 2023 Study region: The Yellow River located in the north of China, the most hyper-concentrated sediment-laden rivers in the world, is featured by complicated spatiotemporal variation of river patterns.
Chaode Yan +6 more
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