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Titlebook: Parallel Problem Solving from Nature, PPSN XI; 11th International C Robert Schaefer,Carlos Cotta,Günter Rudolph Conference proceedings 2010

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發(fā)表于 2025-3-21 19:40:28 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Parallel Problem Solving from Nature, PPSN XI
副標題11th International C
編輯Robert Schaefer,Carlos Cotta,Günter Rudolph
視頻videohttp://file.papertrans.cn/742/741011/741011.mp4
概述Fast conference proceedings.Up to date results.State-of-the-art report
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Parallel Problem Solving from Nature, PPSN XI; 11th International C Robert Schaefer,Carlos Cotta,Günter Rudolph Conference proceedings 2010
出版日期Conference proceedings 2010
關鍵詞agents; algorithms; evolution; evolutionary algorithm; evolutionary computation; grammar; intelligence; lea
版次1
doihttps://doi.org/10.1007/978-3-642-15871-1
isbn_softcover978-3-642-15870-4
isbn_ebook978-3-642-15871-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2010
The information of publication is updating

書目名稱Parallel Problem Solving from Nature, PPSN XI影響因子(影響力)




書目名稱Parallel Problem Solving from Nature, PPSN XI影響因子(影響力)學科排名




書目名稱Parallel Problem Solving from Nature, PPSN XI網(wǎng)絡公開度




書目名稱Parallel Problem Solving from Nature, PPSN XI網(wǎng)絡公開度學科排名




書目名稱Parallel Problem Solving from Nature, PPSN XI被引頻次




書目名稱Parallel Problem Solving from Nature, PPSN XI被引頻次學科排名




書目名稱Parallel Problem Solving from Nature, PPSN XI年度引用




書目名稱Parallel Problem Solving from Nature, PPSN XI年度引用學科排名




書目名稱Parallel Problem Solving from Nature, PPSN XI讀者反饋




書目名稱Parallel Problem Solving from Nature, PPSN XI讀者反饋學科排名




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Parallel Problem Solving from Nature, PPSN XI978-3-642-15871-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Bioreactor Control by Genetic ProgrammingGenetic programming is applied to the problem of bioreactor control. This highly nonlinear problem has previously been suggested as one of the challenging benchmarks to explore new ideas for building automatic controllers. It is shown that the derived control law is successful in a number of test cases.
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A Novel Smart Multi-Objective Particle Swarm Optimisation Using Decompositionposed in MOEA/D, whereby a multi-objective problem (MOP) is represented as several scalar aggregation problems. The scalar aggregation problems are viewed as particles in a swarm; each particle assigns weights to every optimisation objective. The problem is solved then as a Multi-Objective Particle
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