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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… Mehr…

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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… Mehr…

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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… Mehr…

  - 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. Versandkosten:zzgl. Versandkosten.
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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 - Erstausgabe

2010, ISBN: 9783642098765

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Details zum Buch
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.

Detailangaben zum Buch - Linkage in Evolutionary Computation Ying-ping Chen Editor


EAN (ISBN-13): 9783642098765
ISBN (ISBN-10): 3642098762
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: Springer Berlin Heidelberg Core >1 >T
500 Seiten
Gewicht: 0,748 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2011-11-09T00:35:58+01:00 (Berlin)
Detailseite zuletzt geändert am 2020-09-03T23:58:50+02:00 (Berlin)
ISBN/EAN: 3642098762

ISBN - alternative Schreibweisen:
3-642-09876-2, 978-3-642-09876-5
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: ping, chen
Titel des Buches: chen ping


Daten vom Verlag:

Autor/in: Ying-ping Chen
Titel: Studies in Computational Intelligence; Linkage in Evolutionary Computation
Verlag: Springer; Springer Berlin
488 Seiten
Erscheinungsjahr: 2010-10-28
Berlin; Heidelberg; DE
Gedruckt / Hergestellt in Niederlande.
Gewicht: 0,759 kg
Sprache: Englisch
160,49 € (DE)
164,99 € (AT)
177,00 CHF (CH)
POD
XII, 488 p. 227 illus.

BC; Computer-Aided Engineering (CAD, CAE) and Design; 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; Mathematical and Computational Engineering; Artificial Intelligence; Computer-Aided Engineering (CAD, CAE) and Design; Mathematical and Computational Engineering Applications; Artificial Intelligence; Mathematik für Ingenieure; Künstliche Intelligenz; BB

Part I Models & Theories.- Parallel BMDA 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.- Part II Operators & 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.- Part III 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.

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