Results 11 to 20 of about 5,429,485 (293)
An Attribute Reduction Method Using Neighborhood Entropy Measures in Neighborhood Rough Sets [PDF]
Entropy, 2019 Attribute reduction as an important preprocessing step for data mining, and has become a hot research topic in rough set theory. Neighborhood rough set theory can overcome the shortcoming that classical rough set theory may lose some useful information ...
Shiguang Zhang, Jiucheng Xu, Jiucheng Xu
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Reduction of Neighborhood-Based Generalized Rough Sets [PDF]
Journal of Applied Mathematics, 2011 Rough set theory is a powerful tool for dealing with uncertainty, granularity, and incompleteness of knowledge in information systems. This paper discusses five types of existing neighborhood-based generalized rough sets.
Zhaohao Wang, Lan Shu, Xiuyong Ding
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New Neighborhood Based Rough Sets [PDF]
, 2015 Neighborhood based rough sets are important generalizations of the classical rough sets of Pawlak, as neighborhood operators generalize equivalence classes. In this article, we introduce nine neighborhood based operators and we study the partial order relations between twenty-two different neighborhood operators obtained from one covering.
Lynn D'eer, Chris Cornelis
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Information, 2019 Relative reduction of multiple neighborhood-covering with multigranulation rough set has been one of the hot research topics in knowledge reduction theory.
Xiaoying You, Jinjin Li, Hongkun Wang
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Neighborhood Rough Fuzzy Penetration Control Method with Variable Precision Based on GMAW
Applied Sciences, 2023 Considering the nonlinear, time-varying, and multivariate coupling nature of the welding process, achieving excellent control of the welding process can be challenging.
Xiaohong Xiang +7 more
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Characterization of neighborhood operators based on neighborhood relationships
Journal of Intelligent SystemsNeighborhood relationships play a pivotal role in rough set theory, addressing the limitations of equivalence relations. This article focuses on defining upper and lower approximation operators using neighborhood relationships and exploring their ...
Caixin Wei +3 more
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Energies, 2018 In machine learning-based transient stability assessment (TSA) problems, the characteristics of the selected features have a significant impact on the performance of classifiers.
Bingyang Li, Jianmei Xiao, Xihuai Wang
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Feature selection based on neighborhood rough sets and Gini index [PDF]
PeerJ Computer Science, 2023 Neighborhood rough set is considered an essential approach for dealing with incomplete data and inexact knowledge representation, and it has been widely applied in feature selection.
Yuchao Zhang +8 more
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Entropy, 2021 Feature selection is one of the core contents of rough set theory and application. Since the reduction ability and classification performance of many feature selection algorithms based on rough set theory and its extensions are not ideal, this paper ...
Jiucheng Xu +3 more
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Feature Subset Selection Based on Variable Precision Neighborhood Rough Sets
International Journal of Computational Intelligence Systems, 2021 Rough sets have been widely used in the fields of machine learning and feature selection. However, the classical rough sets have the problems of difficultly dealing with real-value data and weakly fault tolerance.
Yingyue Chen, Yumin Chen
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