ISBN: 9783540694328
One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter value… More...
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ISBN: 9783540694328
One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter value… More...
F.J. Lobo; Cláudio F. Lima; Zbigniew Michalewicz:
Parameter Setting in Evolutionary Algorithms - new bookISBN: 9783540694328
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ISBN: 9783540694328
*Parameter Setting in Evolutionary Algorithms* / pdf eBook für 213.99 € / Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Computer & Internet Medien > Bücher nein eBook als pdf eBooks > S… More...
ISBN: 9783540694328
Parameter Setting in Evolutionary Algorithms: ab 213.99 € eBooks > Sachthemen & Ratgeber > Computer & Internet Springer-Verlag GmbH eBook als pdf, Springer-Verlag GmbH
ISBN: 9783540694328
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Details of the book - Parameter Setting in Evolutionary Algorithms
EAN (ISBN-13): 9783540694328
Publisher: Springer-Verlag GmbH
Book in our database since 2016-12-22T11:37:50+00:00 (London)
Detail page last modified on 2024-01-31T13:35:40+00:00 (London)
ISBN/EAN: 9783540694328
ISBN - alternate spelling:
978-3-540-69432-8
Alternate spelling and related search-keywords:
Book author: zbigniew
Information from Publisher
Author: F.J. Lobo; Cláudio F. Lima; Zbigniew Michalewicz
Title: Studies in Computational Intelligence; Parameter Setting in Evolutionary Algorithms
Publisher: Springer; Springer Berlin
318 Pages
Publishing year: 2007-04-03
Berlin; Heidelberg; DE
Language: English
213,99 € (DE)
220,00 € (AT)
236,00 CHF (CH)
Available
XII, 318 p. 100 illus.
EA; E107; eBook; Nonbooks, PBS / Technik/Allgemeines, Lexika; Mathematik für Ingenieure; Verstehen; algorithm; algorithms; calculus; control; evolution; evolutionary algorithm; evolutionary computation; evolutionary strategies; genetic algorithms; genetic programming; multi-objective optimization; mutation; operator; optimization; programming; C; Mathematical and Computational Engineering Applications; Artificial Intelligence; Engineering; Künstliche Intelligenz; BC
Parameter Setting in EAs: a 30 Year Perspective.- Parameter Control in Evolutionary Algorithms.- Self-Adaptation in Evolutionary Algorithms.- Adaptive Strategies for Operator Allocation.- Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms.- Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks.- Genetic Programming: Parametric Analysis of Structure Altering Mutation Techniques.- Parameter Sweeps for Exploring Parameter Spaces of Genetic and Evolutionary Algorithms.- Adaptive Population Sizing Schemes in Genetic Algorithms.- Population Sizing to Go: Online Adaptation Using Noise and Substructural Measurements.- Parameter-less Hierarchical Bayesian Optimization Algorithm.- Evolutionary Multi-Objective Optimization Without Additional Parameters.- Parameter Setting in Parallel Genetic Algorithms.- Parameter Control in Practice.- Parameter Adaptation for GP Forecasting Applications.Recent advances in evolutionary algorithms Includes supplementary material: sn.pub/extras
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