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Titlebook: Multiobjective Genetic Algorithms for Clustering; Applications in Data Ujjwal Maulik,Sanghamitra Bandyopadhyay,Anirban Mu Textbook 2011 Spr

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发表于 2025-3-21 19:10:22 | 显示全部楼层 |阅读模式
书目名称Multiobjective Genetic Algorithms for Clustering
副标题Applications in Data
编辑Ujjwal Maulik,Sanghamitra Bandyopadhyay,Anirban Mu
视频video
概述Book introduces many original ideas.Significant contribution to the field.Authors detail collaborations in biological and data mining applications
图书封面Titlebook: Multiobjective Genetic Algorithms for Clustering; Applications in Data Ujjwal Maulik,Sanghamitra Bandyopadhyay,Anirban Mu Textbook 2011 Spr
描述.This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries..The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience..
出版日期Textbook 2011
关键词Bioinformatics; Clustering; Computational Biology; Data Mining; Genetic Algorithms; Geoscience; Multiobjec
版次1
doihttps://doi.org/10.1007/978-3-642-16615-0
isbn_softcover978-3-642-43963-6
isbn_ebook978-3-642-16615-0
copyrightSpringer-Verlag Berlin Heidelberg 2011
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Textbook 2011ies..The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience..
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Textbook 2011 and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of d
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