Results 41 to 50 of about 3,498,542 (196)
Incremental Algorithm for Attribute Reduction Based on Positive Region and Discernibility Element [PDF]
Jisuanji gongcheng, 2016 The reduction result should be updated continually with the dynamic changing of data in decision table.In order to improve the efficiency of attribute reduction while ensuring the simplest results,an improved decision table reduction algorithm is ...
LIU Taotao,MA Fumin,ZHANG Tengfei
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A Novel Multi-Criteria Decision-Making Method Based on Rough Sets and Fuzzy Measures
Axioms, 2022 Rough set theory provides a useful tool for data analysis, data mining and decision making. For multi-criteria decision making (MCDM), rough sets are used to obtain decision rules by reducing attributes and objects.
Jingqian Wang, Xiaohong Zhang
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Entropy, 2023 Telecom fraud detection is of great significance in online social networks. Yet the massive, redundant, incomplete, and uncertain network information makes it a challenging task to handle.
Ran Li +5 more
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Heuristic Approaches to Attribute Reduction for Generalized Decision Preservation
Applied Sciences, 2019 Attribute reduction is a challenging problem in rough set theory, which has been applied in many research fields, including knowledge representation, machine learning, and artificial intelligence.
Nan Zhang, Xueyi Gao, Tianyou Yu
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Incremental Attribute Reduction Based on Simplified Discernibility Matrix
工程科学与技术, 2013 :In order to update the attribute reduction of decision table dynamically, the definitions of the simplified decision table and attribute reduction based on simplified discernibility matrix were proposed.
葛浩, 李龙澍, 杨传健
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Shuju Caiji Yu ChuliAccuracy and efficiency are the key metrics for evaluating the performance of feature selection algorithms. They correspond to the attribute dependence and reduction scale of neighborhood rough sets respectively. Conventional feature selection algorithms
LUO Gongzhi, ZHANG Shanglei
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New Measures of Uncertainty for Interval-Valued Data With Application to Attribute Reduction
IEEE Access, 2022 Uncertainty measurement (UM) gives a brand-new perspective on attribute reduction in an information system (IS). Interval-valued data is a kind of very vital data in rough set theory (RST).
Lulu Li
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Incremental attribute reduction in incomplete decision systems
, 2012 According to whether the underlying information decision system varies with time, methods for attribute reduction can be categoried as static and dynamic two groups.
Hong Shen, Wenhao Shu, Shu, W., Shen, H.
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Two‐step attribute reduction for AIoT networks
IET CommunicationsThe evolution of Artificial Intelligence of Things (AIoT) pushes connectivity from human‐to‐things and things‐to‐things, to AI‐to‐things, has resulted in more complex physical networks and logical associations.
Chao Ren +5 more
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Neighbourhood systems based attribute reduction in formal decision contexts
CAAI Transactions on Intelligence Technology, 2019 Attribute reduction of formal decision context mainly uses the relationship between two concept lattices generated by the condition and decision attributes to remove redundant condition attributes.
Xiaohe Zhang +3 more
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