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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?yàn)g覽 |閱讀模式
書(shū)目名稱Parallel Problem Solving from Nature, PPSN XI
副標(biāo)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(shū)名稱Lecture Notes in Computer Science
圖書(shū)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(guān)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(shū)目名稱Parallel Problem Solving from Nature, PPSN XI影響因子(影響力)




書(shū)目名稱Parallel Problem Solving from Nature, PPSN XI影響因子(影響力)學(xué)科排名




書(shū)目名稱Parallel Problem Solving from Nature, PPSN XI網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Parallel Problem Solving from Nature, PPSN XI網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Parallel Problem Solving from Nature, PPSN XI被引頻次




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Parallel Problem Solving from Nature, PPSN XI978-3-642-15871-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
地板
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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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