Results 21 to 30 of about 140,208 (262)
NOx Emission Prediction of Coal Fired Utility Boiler Based on FAR-HK-ELM
Taiyuan Ligong Daxue xuebao, 2021 A prediction method for NOx emission of coal-fired utility boiler based on FAR-HK-ELM was proposed by combining the Fast Attribute Reduction (FAR) and Hybrid Kernel Extreme Learning Machine (HK-ELM) algorithms.
Wenhua FU +4 more
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Attributes Reduction in Big Data [PDF]
Applied Sciences, 2020 Processing big data requires serious computing resources. Because of this challenge, big data processing is an issue not only for algorithms but also for computing resources. This article analyzes a large amount of data from different points of view.
Waleed Albattah +2 more
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Coevolutionary Fuzzy Attribute Order Reduction With Complete Attribute-Value Space Tree [PDF]
IEEE Transactions on Emerging Topics in Computational Intelligence, 2021 Since big data sets are structurally complex, high-dimensional, and their attributes exhibit some redundant and irrelevant information, the selection, evaluation, and combination of those large-scale attributes pose huge challenges to traditional methods. Fuzzy rough sets have emerged as a powerful vehicle to deal with uncertain and fuzzy attributes in
Weiping Ding +2 more
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Research on Attribute Reduction Algorithm in Aquatic Product Safety Assessment System [PDF]
Jisuanji gongcheng, 2016 Aiming at the complexity and redundancy of the evaluation index in the aquatic product safety assessment system,a new attribute reduction algorithm based on attribute unimportance is proposed.The algorithm uses the method of fusing the positive region ...
E Xu,TAN Yan,LI Jianrong,MAO Meijing,YANG Mingjing
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International Journal of Approximate Reasoning, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Xianyong, Miao, Duoqian
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Neighborhood conditional mutual information entropy attribute reduction algorithm for hybrid data
大数据, 2022 Attribute reduction is an important research content of the rough set theory.Its main purpose is to eliminate irrelevant attributes in information systems, reduce data dimensions and improve data knowledge discovery performance.However, most of the ...
Haibo LAN
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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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Efficient Attribute Reduction Algorithm [PDF]
, 2004 Efficiency of algorithms is always an important issue concerned by so many researchers. Rough set theory is a valid tool to deal with imprecise problems. However, some of its algorithms’ consuming time limits the applications of rough set. According to this, our paper analyzes the reasons of rough set algorithms’ inefficiency by focusing on two ...
Zhongzhi Shi, Shaohui Liu, Zheng Zheng
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Reduct-based ranking of attributes
Procedia Computer Science, 2020 Abstract The paper is dedicated to the area of feature selection, in particular a notion of attribute rankings that allow to estimate importance of variables. In the research presented for ranking construction a new weighting factor was defined, based on relative reducts.
Zielosko, Beata, Stańczyk, Urszula
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