Cantitate/Preț
Produs
Total produse
Vezi coșul
Hybrid Evolutionary Algorithms de Crina Grosan

Hybrid Evolutionary Algorithms

Editat de Crina Grosan, Ajith Abraham, Hisao Ishibuchi
en Limba Engleză Hardback – 19 sep 2007
Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in “Hybrid Evolutionary Algorithms”. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 95450 lei  43-57 zile
  Springer Berlin, Heidelberg – 16 noi 2010 95450 lei  43-57 zile
Hardback (1) 96177 lei  43-57 zile
  Springer – 19 sep 2007 96177 lei  43-57 zile

Preț: 96177 lei

Preț vechi: 120222 lei
-20%

Puncte Express: 1443
Preț estimativ în valută:
17025€ • 19775$ • 14750£

Carte tipărită la comandă

Livrare economică 02-16 martie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783540732969
ISBN-10: 3540732969
Pagini: 420
Ilustrații: XV, 404 p.
Dimensiuni: 160 x 241 x 29 mm
Greutate: 0.79 kg
Ediția:2007
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews.- Quantum-Inspired Evolutionary Algorithm for Numerical Optimization.- Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective.- Hybrid Evolutionary Algorithms and Clustering Search.- A Novel Hybrid Algorithm for Function Optimization: Particle Swarm Assisted Incremental Evolution Strategy.- An Efficient Nearest Neighbor Classifier.- Hybrid Genetic: Particle Swarm Optimization Algorithm.- A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection.- Memetic Algorithms Parametric Optimization for Microlithography.- Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction.- A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids.- Clustering Gene-Expression Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search.- Robust Parametric Image Registration.- Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP.

Textul de pe ultima copertă

Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in ’Hybrid Evolutionary Algorithms’. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.

Caracteristici

Reports recent research results on Hybrid Evolutionary Algorithms