Theoretical Aspects of Evolutionary Computing: Natural Computing Series
Editat de Leila Kallel, Bart Naudts, Alex Rogersen Limba Engleză Paperback – 7 dec 2010
Toate formatele și edițiile | Preț | Express |
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Paperback (1) | 977.35 lei 6-8 săpt. | |
Springer Berlin, Heidelberg – 7 dec 2010 | 977.35 lei 6-8 săpt. | |
Hardback (1) | 983.16 lei 6-8 săpt. | |
Springer Berlin, Heidelberg – 8 mai 2001 | 983.16 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783642086762
ISBN-10: 3642086764
Pagini: 512
Ilustrații: X, 499 p.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.71 kg
Ediția:Softcover reprint of hardcover 1st ed. 2001
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Natural Computing Series
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642086764
Pagini: 512
Ilustrații: X, 499 p.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.71 kg
Ediția:Softcover reprint of hardcover 1st ed. 2001
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Natural Computing Series
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
Professional/practitionerCuprins
I: Tutorials.- to Evolutionary Computing in Design Search and Optimisation.- Evolutionary Algorithms and Constraint Satisfaction: Definitions, Survey, Methodology, and Research Directions.- The Dynamical Systems Model of the Simple Genetic Algorithm.- Modelling Genetic Algorithm Dynamics.- Statistical Mechanics Theory of Genetic Algorithms.- Theory of Evolution Strategies — A Tutorial.- Evolutionary Algorithms: From Recombination to Search Distributions.- Properties of Fitness Functions and Search Landscapes.- II: Technical Papers.- A Solvable Model of a Hard Optimisation Problem.- Bimodal Performance Profile of Evolutionary Search and the Effects of Crossover.- Evolution Strategies in Noisy Environments — A Survey of Existing Work.- Cyclic Attractors and Quasispecies Adaptability.- Genetic Algorithms in Time-Dependent Environments.- Statistical Machine Learning and Combinatorial Optimization.- Multi-Parent Scanning Crossover and Genetic Drift.- Harmonic Recombination for Evolutionary Computation.- How to Detect all Maxima of a Function.- On Classifications of Fitness Functions.- Genetic Search on Highly Symmetric Solution Spaces: Preliminary Results.- Structure Optimization and Isomorphisms.- Detecting Spin-Flip Symmetry in Optimization Problems.- Asymptotic Results for Genetic Algorithms with Applications to Nonlinear Estimation.
Caracteristici
A self-contained snapshot of the state of the art in the theory of Evolutionary Computing Gives an overview of differing approaches to the theory of Evolutionary Algorithms With extensive entry level tutorials written by leading experts in the field Includes supplementary material: sn.pub/extras