Engineering Evolutionary Intelligent Systems / Edition 1

Engineering Evolutionary Intelligent Systems / Edition 1

by Ajith Abraham
     
 

ISBN-10: 364209466X

ISBN-13: 9783642094668

Pub. Date: 11/19/2010

Publisher: Springer Berlin Heidelberg

This edited volume deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business and commerce. It comprises 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges.

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Overview

This edited volume deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business and commerce. It comprises 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.

Product Details

ISBN-13:
9783642094668
Publisher:
Springer Berlin Heidelberg
Publication date:
11/19/2010
Series:
Studies in Computational Intelligence Series, #82
Edition description:
Softcover reprint of hardcover 1st ed. 2008
Pages:
444
Product dimensions:
6.14(w) x 9.21(h) x 0.94(d)

Table of Contents

Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews.- Genetically Optimized Hybrid Fuzzy Neural Networks: Analysis and Design of Rule-based Multi-layer Perceptron Architectures.- Genetically Optimized Self-organizing Neural Networks Based on Polynomial and Fuzzy Polynomial Neurons: Analysis and Design.- Evolution of Inductive Self-organizing Networks.- Recursive Pattern based Hybrid Supervised Training.- Enhancing Recursive Supervised Learning Using Clustering and Combinatorial Optimization (RSL-CC).- Evolutionary Approaches to Rule Extraction from Neural Networks.- Cluster-wise Design of Takagi and Sugeno Approach of Fuzzy Logic Controller.- Evolutionary Fuzzy Modelling for Drug Resistant HIV-1 Treatment Optimization.- A New Genetic Approach for Neural Network Design.- A Grammatical Genetic Programming Representation for Radial Basis Function Networks.- A Neural-Genetic Technique for Coastal Engineering: Determining Wave-induced Seabed Liquefaction Depth.- On the Design of Large-scale Cellular Mobile Networks Using Multi-population Memetic Algorithms.- A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem.- Particle Swarm Optimization with Mutation for High Dimensional Problems.

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