Advances in Evolutionary Computing for System Design

Overview

Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book’s thirteen chapters cover a wide area of topics in evolutionary computing and applications, including an introduction to evolutionary computing in system design; evolutionary neuro-fuzzy systems; and evolution of fuzzy controllers. The book will be useful to researchers in intelligent systems with interest in evolutionary computing, as well as application engineers ...

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Paperback (Softcover reprint of hardcover 1st ed. 2007)
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Overview

Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book’s thirteen chapters cover a wide area of topics in evolutionary computing and applications, including an introduction to evolutionary computing in system design; evolutionary neuro-fuzzy systems; and evolution of fuzzy controllers. The book will be useful to researchers in intelligent systems with interest in evolutionary computing, as well as application engineers and system designers.

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Product Details

  • ISBN-13: 9783642091445
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 11/25/2010
  • Series: Studies in Computational Intelligence Series , #66
  • Edition description: Softcover reprint of hardcover 1st ed. 2007
  • Edition number: 1
  • Pages: 326
  • Product dimensions: 0.70 (w) x 6.14 (h) x 9.21 (d)

Table of Contents

to Evolutionary Computing in System Design.- Evolutionary Neuro-Fuzzy Systems and Applications.- Evolution of Fuzzy Controllers and Applications.- A Neuro-Genetic Framework for Multi-Classifier Design: An Application to Promoter Recognition in DNA Sequences.- Evolutionary Grooming of Traffic in WDM Optical Networks.- EPSO: Evolutionary Particle Swarms.- Design of Type-Reduction Strategies for Type-2 Fuzzy Logic Systems using Genetic Algorithms.- Designing a Recurrent Neural Network-based Controller for Gyro-Mirror Line-of-Sight Stabilization System using an Artificial Immune Algorithm.- Distributed Problem Solving using Evolutionary Learning in Multi-Agent Systems.- Evolutionary Computing within Grid Environment.- Application of Evolutionary Game Theory to Wireless Mesh Networks.- Applying Hybrid Multiobjective Evolutionary Algorithms to the Sailor Assignment Problem.- Evolutionary Techniques Applied to Hardware Optimization Problems: Test and Verification of Advanced Processors.

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