Advances in Evolutionary Computing for System Design

Jain, Lakhmi; Palade, Vasile; Srinivasan, Dipti (eds)

ISBN 10: 3540723765 ISBN 13: 9783540723769

Editore: Springer Verlag, Secaucus, 2007

Lingua: Inglese

Condizione: Usato - Molto buono Rilegato

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Titolo

Advances in Evolutionary Computing for System Design

Editore

Springer Verlag, Secaucus

Data di pubblicazione

2007

Lingua

Inglese

ISBN 10

3540723765

ISBN 13

9783540723769

Rilegatura

Hardcover

Condizione

Very Good

Condizione della sovraccoperta

No Jacket

Cataloghi dei venditori

Mathematics

Descrizione articolo

Riassunto

Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: Introduction to evolutionary computing in system design; evolutionary neuro-fuzzy systems; evolution of fuzzy controllers; genetic algorithms for multi-classifier design; evolutionary grooming of traffic; evolutionary particle swarms; fuzzy logic systems using genetic algorithms; evolutionary algorithms and immune learning for neural network-based controller design; distributed problem solving using evolutionary learning; evolutionary computing within grid environment; evolutionary game theory in wireless mesh networks; hybrid multiobjective evolutionary algorithms for the sailor assignment problem; evolutionary techniques in hardware optimization. This book will be useful to researchers in intelligent systems with interest in evolutionary computing, application engineers and system designers. The book can also be used by students and lecturers as an advanced reading material for courses on evolutionary computing.

Dalla quarta di copertina

Introduction to evolutionary computing in system design
Evolutionary neuro-fuzzy systems
Evolution of fuzzy controllers
Genetic algorithms for multi-classifier design
Evolutionary grooming of traffic
Evolutionary particle swarms
Fuzzy logic systems using genetic algorithms
Evolutionary algorithms and immune learning for neural network-based controller design
Distributed problem solving using evolutionary learning
Evolutionary computing within grid environment
Evolutionary game theory in wireless mesh networks
Hybrid multiobjective evolutionary algorithms for the sailor assignment problem
Evolutionary techniques in hardware optimization

This book will be useful to researchers in intelligent systems with interest in evolutionary computing, application engineers and system designers. The book can also be used by students and lecturers as an advanced reading material for courses on evolutionary computing.

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