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On Topological Properties of Generalized Rough Approximation Operators [PDF]
Jisuanji kexue, 2022 Rough set theory is a mathematical tool for dealing with uncertain information.The core notions of rough set theory is approximation operators of approximation spaces.Pawlak approximation operators are established by using equivalence relations on the ...
LI Yan-yan, QIN Ke-yun
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Attribute Reduction of Boolean Matrix in Neighborhood Rough Set Model
International Journal of Computational Intelligence Systems, 2020 Neighborhood rough set is a powerful tool to deal with continuous value information systems. Graphics processing unit (GPU) computing can efficiently accelerate the calculation of the attribute reduction and approximation sets based on matrix.
Yan Gao, Changwei Lv, Zhengjiang Wu
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IEEE Access, 2020 Neighborhood rough model is widely used in feature selection with high dimension, fuzzy, continuous and discrete attributes, incomplete data and so on, and the application of neighborhood rough model depends on neighborhood threshold.
Yanan Hu +4 more
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An Ensemble Classification Method for High-Dimensional Data Using Neighborhood Rough Set
Complexity, 2021 Mining useful knowledge from high-dimensional data is a hot research topic. Efficient and effective sample classification and feature selection are challenging tasks due to high dimensionality and small sample size of microarray data.
Jing Zhang +3 more
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Five Generalized Rough Approximation Spaces Produced by Maximal Rough Neighborhoods
, 2023 In rough set theory, the multiplicity of methods of calculating neighborhood systems is very useful to calculate the measures of accuracy and roughness.
A. A. Azzam, Tareq M. Al-shami
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Multi-Label Attribute Reduction Based on Variable Precision Fuzzy Neighborhood Rough Set
IEEE Access, 2020 Multi-label attribute reduction as a common dimensionality reduction technique has obtained widely research in recent years. Most existing multi-label attribute reduction methods adopt discretization to deal with mixed data and have strict requirements ...
Panpan Chen, Menglei Lin, Jinghua Liu
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Complex & Intelligent Systems, 2023 Fuzzy rough set models are useful tools for dealing with fuzzy and real-valued data. They have been used in many real-world applications. In this paper, we investigate the fuzzy rough set model based on triangular norms and fuzzy implications.
Zhaohao Wang
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, 2022 Due to the increasing complexity of the entire satellite system and the deteriorating orbital environment, multiple independent single faults may occur simultaneously in the satellite power system.
Chen Lu +7 more
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Six-Set Approximation Theorem of neighborhood related rough sets
International Journal of Approximate Reasoning, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liwen Ma, Hui Lu
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Intuitionistic Fuzzy Neighborhood Rough Set Model for Feature Selection
, 2018 Feature selection is one of the widely used pre-processing techniques to deal with large data sets. In this context, rough set theory has been successfully implemented for feature selection of discrete data set but in case of continuous data set it ...
Anoop Kumar Tiwari +2 more
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