Results 11 to 20 of about 1,718,703 (323)
Cost-sensitive Multigranulation Approximation of Neighborhood Rough Fuzzy Sets [PDF]
Jisuanji kexue, 2023 Multigranulation neighborhood rough sets are a new data processing mode in the theory of neighborhood rough sets,in which the target concept can be characterized by upper/lower approximate boundaries of optimistic and pessimistic,respectively ...
YANG Jie, KUANG Juncheng, WANG Guoyin, LIU Qun
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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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On Covering-Based Rough Intuitionistic Fuzzy Sets
Mathematics, 2022 Intuitionistic Fuzzy Sets (IFSs) and rough sets depending on covering are important theories for dealing with uncertainty and inexact problems. We think the neighborhood of an element is more realistic than any cluster in the processes of classification ...
R. Mareay +3 more
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Grid service discovery with rough sets [PDF]
, 2008 Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Wang, Z +7 more
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Weak Label Feature Selection Method Based on Neighborhood Rough Sets and Relief [PDF]
Jisuanji kexue, 2022 In multi-label learning and classification, existing feature selection algorithms based on neighborhood rough sets will use classification margin of samples as the neighborhood radius.However, when the margin is too large, the classification may be ...
SUN Lin, HUANG Miao-miao, XU Jiu-cheng
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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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Journal of Mathematics, 2021 Multigranulation rough set theory is an important tool to deal with the problem of multicriteria information system. The notion of fuzzy β-neighborhood has been used to construct some covering-based multigranulation fuzzy rough set (CMFRS) models through
Zaibin Chang, Lingling Mao
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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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Single-Valued Neutrosophic Covering-Based Rough Set Model Over Two Universes and Its Application in MCDM [PDF]
Neutrosophic Sets and Systems, 2023 This article aims to propose a new type of single-valued neutrosophic(SVN) covering-based rough sets over two universes by using Wang’s single-valued neutrosophic covering rough sets.
Somen Debnath
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Covering Fuzzy Rough Sets via Variable Precision
Journal of Mathematics, 2021 Lately, covering fuzzy rough sets via variable precision according to a fuzzy γ-neighborhood were established by Zhan et al. model. Also, Ma et al. gave the definition of complementary fuzzy γ-neighborhood with reflexivity.
Mohammed Atef, A. A. Azzam
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