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Linkage in Evolutionary Computation - Ying-ping Chen (Editor)
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Linkage in Evolutionary Computation - nuovo livro

ISBN: 9783642098765

In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to c… mais…

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Linkage in Evolutionary Computation Ying-ping Chen Editor
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Linkage in Evolutionary Computation Ying-ping Chen Editor - nuovo livro

ISBN: 9783642098765

In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to c… mais…

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Linkage in Evolutionary Computation - Ying-ping Chen
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Ying-ping Chen:
Linkage in Evolutionary Computation - nuovo livro

ISBN: 9783642098765

Computer Science; Computer-Aided Engineering (CAD, CAE) and Design; Mathematical and Computational Engineering; Artificial Intelligence (incl. Robotics) Bayesian network, Evolution, Evolu… mais…

  - This volume presents recent results in Linkage in Evolutionary Computation. For practitioners who are looking at putting into practice the concept of linkage, the few chapters on applications will serve as a useful guide. Custos de envio:zzgl. Versandkosten., mais custos de envio
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Ying-ping Chen:
Linkage in Evolutionary Computation - Livro de bolso

ISBN: 9783642098765

Linkage in Evolutionary Computation Linkage-in-Evolutionary-Computation~~Ying-ping-Chen Science>Mathematics>Mathematics Paperback, Springer Berlin Heidelberg

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Ying-ping Chen:
Linkage in Evolutionary Computation - primeira edição

2010, ISBN: 9783642098765

Livro de bolso, Edição encadernada

[ED: 1], 1., Softcover reprint of hardcover 1st ed. 2008, Softcover, Buch, [PU: Springer Berlin]

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Linkage in Evolutionary Computation Ying-ping Chen Editor

In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based approaches have their limits; they can be easily "fooled" by cases of triviality or peculiarity of the class of problems that the algorithms are designed to handle. Furthermore, these approaches are usually blind to the interactions between the decision variables, thereby disrupting the partial solutions that are being built up along the way.

Dados detalhados do livro - Linkage in Evolutionary Computation Ying-ping Chen Editor


EAN (ISBN-13): 9783642098765
ISBN (ISBN-10): 3642098762
Livro de capa dura
Livro de bolso
Ano de publicação: 2010
Editor/Editora: Springer Berlin Heidelberg Core >1 >T
500 Páginas
Peso: 0,748 kg
Língua: eng/Englisch

Livro na base de dados desde 2011-11-08T21:35:58-02:00 (Sao Paulo)
Página de detalhes modificada pela última vez em 2020-09-03T18:58:50-03:00 (Sao Paulo)
Número ISBN/EAN: 9783642098765

Número ISBN - Ortografia alternativa:
3-642-09876-2, 978-3-642-09876-5
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: ping, chen
Título do livro: chen ping


Dados da editora

Autor: Ying-ping Chen
Título: Studies in Computational Intelligence; Linkage in Evolutionary Computation
Editora: Springer; Springer Berlin
488 Páginas
Ano de publicação: 2010-10-28
Berlin; Heidelberg; DE
Impresso / Feito em
Língua: Inglês
160,49 € (DE)
164,99 € (AT)
177,00 CHF (CH)
POD
XII, 488 p. 227 illus.

BC; Hardcover, Softcover / Informatik, EDV/Anwendungs-Software; Computer-Aided Design (CAD); Verstehen; Bayesian network; Evolution; Evolutionary Computation; Linkage; Operator; algorithm; algorithms; calculus; cognition; evolutionary algorithm; genetic algorithms; learning; microelectromechanical system (MEMS); model; optimization; Computer-Aided Engineering (CAD, CAE) and Design; Mathematical and Computational Engineering Applications; Artificial Intelligence; Mathematik für Ingenieure; Künstliche Intelligenz; BB; EA

Models and Theories.- Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration.- Linkages Detection in Histogram-Based Estimation of Distribution Algorithm.- Linkage in Island Models.- Real-Coded ECGA for Solving Decomposable Real-Valued Optimization Problems.- Linkage Learning Accuracy in the Bayesian Optimization Algorithm.- The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks.- Linkage Learning in Estimation of Distribution Algorithms.- Operators and Frameworks.- Parallel GEAs with Linkage Analysis over Grid.- Identification and Exploitation of Linkage by Means of Alternative Splicing.- A Clustering-Based Approach for Linkage Learning Applied to Multimodal Optimization.- Studying the Effects of Dual Coding on the Adaptation of Representation for Linkage in Evolutionary Algorithms.- Symbiotic Evolution to Avoid Linkage Problem.- EpiSwarm, a Swarm-Based System for Investigating Genetic Epistasis.- Real-Coded Extended Compact Genetic Algorithm Based on Mixtures of Models.- Applications.- Genetic Algorithms for the Airport Gate Assignment: Linkage, Representation and Uniform Crossover.- A Decomposed Approach for the Minimum Interference Frequency Assignment.- Set Representation and Multi-parent Learning within an Evolutionary Algorithm for Optimal Design of Trusses.- A Network Design Problem by a GA with Linkage Identification and Recombination for Overlapping Building Blocks.- Knowledge-Based Evolutionary Linkage in MEMS Design Synthesis.
Presents recent results in Linkage in Evolutionary Computation

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