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Linkage in Evolutionary Computation - Ying-ping Chen (Editor)
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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… Plus…

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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… Plus…

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

  - 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. Frais d'envoizzgl. Versandkosten., Livraison non-comprise
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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 - Première édition

2010, ISBN: 9783642098765

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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.

Informations détaillées sur le livre - Linkage in Evolutionary Computation Ying-ping Chen Editor


EAN (ISBN-13): 9783642098765
ISBN (ISBN-10): 3642098762
Version reliée
Livre de poche
Date de parution: 2010
Editeur: Springer Berlin Heidelberg Core >1 >T
500 Pages
Poids: 0,748 kg
Langue: eng/Englisch

Livre dans la base de données depuis 2011-11-09T00:35:58+01:00 (Zurich)
Page de détail modifiée en dernier sur 2020-09-03T23:58:50+02:00 (Zurich)
ISBN/EAN: 3642098762

ISBN - Autres types d'écriture:
3-642-09876-2, 978-3-642-09876-5
Autres types d'écriture et termes associés:
Auteur du livre: ping, chen
Titre du livre: chen ping


Données de l'éditeur

Auteur: Ying-ping Chen
Titre: Studies in Computational Intelligence; Linkage in Evolutionary Computation
Editeur: Springer; Springer Berlin
488 Pages
Date de parution: 2010-10-28
Berlin; Heidelberg; DE
Imprimé / Fabriqué en
Langue: Anglais
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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