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Titlebook: Genetic Algorithms for Applied CAD Problems; Viktor M. Kureichik,Sergey P. Malioukov,Alexander Book 2009 Springer-Verlag Berlin Heidelber

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發(fā)表于 2025-3-21 18:34:24 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Genetic Algorithms for Applied CAD Problems
編輯Viktor M. Kureichik,Sergey P. Malioukov,Alexander
視頻videohttp://file.papertrans.cn/383/382439/382439.mp4
概述Presents important applications of Genetic Algorithms for CAD Problems
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Genetic Algorithms for Applied CAD Problems;  Viktor M. Kureichik,Sergey P. Malioukov,Alexander  Book 2009 Springer-Verlag Berlin Heidelber
描述.New perspective technologies of genetic search and evolution simulation represent the kernel of this book. The authors wanted to show how these technologies are used for practical problems solution. This monograph is devoted to specialists of CAD, intellectual information technologies in science, biology, economics, sociology and others. It may be used by post-graduate students and students of specialties connected to the systems theory and system analysis methods, information science, optimization methods, operations investigation and solution-making..
出版日期Book 2009
關鍵詞Racter; algorithms; computer-aided design (CAD); design; evolution; genetic algorithm; kernel; optimization
版次1
doihttps://doi.org/10.1007/978-3-540-85281-0
isbn_softcover978-3-642-24257-1
isbn_ebook978-3-540-85281-0Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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Evolutionary Models of Decision Making,on, proposed by Charles Darwin, provides a structure for the process, in which the individuals of some population, endowed with some higher functional properties, have higher chances of reproduction, than the “weak” individuals. Such mechanism is named frequently the “survivals of the strongest”.
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Development of Genetic Algorithms for Finding Optimal Magnetic Head Parameters and Characteristics,s differ from other methods of optimization and search [88, 109]. Genetic algorithms:.In GA the input parameters are first analyzed and a set of alternative solutions called population is generated. Each solution is encoded as a finite sequence in some alphabet. GA works until solution of desired qu
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https://doi.org/10.1007/978-1-4842-4379-4tages: systems engineering, circuit engineering and design..The first stage includes the system and structure design. The second stage - schematic design - consists of simulation, logical design, control and diagnostic test building. The third stage includes the engineering and technological design.
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Syringocystadenoma Papilliferumonents of the device designed..The routing problem is among the most difficult ones in the automated ECE design. This is connected with several factors, particularly with the variety of connection methods. Each connection method has different optimization criteria and limitations. From the mathemati
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Hands-On Guide for Ex Vivo Confocal Imagings differ from other methods of optimization and search [88, 109]. Genetic algorithms:.In GA the input parameters are first analyzed and a set of alternative solutions called population is generated. Each solution is encoded as a finite sequence in some alphabet. GA works until solution of desired qu
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