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Titlebook: Advanced Computational Methods for Knowledge Engineering; Ngoc Thanh Nguyen,Tien Do,Hoai An Thi Conference proceedings 2013 Springer Inter

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發(fā)表于 2025-3-21 17:10:15 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advanced Computational Methods for Knowledge Engineering
影響因子2023Ngoc Thanh Nguyen,Tien Do,Hoai An Thi
視頻videohttp://file.papertrans.cn/146/145334/145334.mp4
發(fā)行地址Presents Advanced Computational Methods for Knowledge Engineering.Edited outcome of the 1st International Conference on Computer Science, Applied Mathematics and Applications ICCSMA 2013, held in Wars
學(xué)科分類Studies in Computational Intelligence
圖書封面Titlebook: Advanced Computational Methods for Knowledge Engineering;  Ngoc Thanh Nguyen,Tien Do,Hoai An Thi Conference proceedings 2013 Springer Inter
影響因子The book consists of 29 extended chapters which have been selected and invited from the submissions to the .1.st. International Conference on Computer Science, Applied Mathematics and Applications. (ICCSAMA 2013) held on 9-10 May, 2013 in Warsaw, Poland. The book is organized into five parts, which are: Advanced Optimization Methods and Their Applications, Queuing Theory and Applications, Computational Methods for Knowledge Engineering, Knowledge Engineering with Cloud and Grid Computing, and Logic Based Methods for Decision Making and Data Mining, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering.
Pindex Conference proceedings 2013
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Zur Grundlage des Formens mit Sandslingern, DC (Difference of Convex functions) programs for which DC programming and DC Algorithms (DCA) are investigated. The preliminary numerical experiments on real-world datasets show the efficiency and the superiority of our methods versus one of the best standard algorithms on booth feature selection and classification.
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https://doi.org/10.1007/978-3-662-26643-4lving this problem, we propose a column generation approach, where the label correcting method is used to treat the sub-problem. The efficiency of our approach is evaluated by comparing with solution given by CPLEX on different scenarios.
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https://doi.org/10.1007/978-3-662-29324-9nd computing for determining the relative density of sands using CPT data. It helps us to reach unknown reality through . measures and ‘true-false’ analysis using the meta-concept, “.”, rather than approximation of the known reality through degrees of truth and ‘degree of truth’ analysis.
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