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Engineering Evolutionary Intelligent Systems

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Cover of 'Engineering Evolutionary Intelligent Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews
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    Chapter 2 Genetically Optimized Hybrid Fuzzy Neural Networks: Analysis and Design of Rule-based Multi-layer Perceptron Architectures
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    Chapter 3 Genetically Optimized Self-organizing Neural Networks Based on Polynomial and Fuzzy Polynomial Neurons: Analysis and Design
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    Chapter 4 Evolution of Inductive Self-organizing Networks
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    Chapter 5 Recursive Pattern based Hybrid Supervised Training
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    Chapter 6 Enhancing Recursive Supervised Learning Using Clustering and Combinatorial Optimization (RSL-CC)
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    Chapter 7 Evolutionary Approaches to Rule Extraction from Neural Networks
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    Chapter 8 Cluster-wise Design of Takagi and Sugeno Approach of Fuzzy Logic Controller
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    Chapter 9 Evolutionary Fuzzy Modelling for Drug Resistant HIV-1 Treatment Optimization
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    Chapter 10 A New Genetic Approach for Neural Network Design
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    Chapter 11 A Grammatical Genetic Programming Representation for Radial Basis Function Networks
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    Chapter 12 A Neural-Genetic Technique for Coastal Engineering: Determining Wave-induced Seabed Liquefaction Depth
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    Chapter 13 On the Design of Large-scale Cellular Mobile Networks Using Multi-population Memetic Algorithms
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    Chapter 14 A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem
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    Chapter 15 Particle Swarm Optimization with Mutation for High Dimensional Problems
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Title
Engineering Evolutionary Intelligent Systems
Published by
Springer Science & Business Media, January 2008
DOI 10.1007/978-3-540-75396-4
ISBNs
978-3-54-075395-7, 978-3-54-075396-4
Editors

Abraham, Ajith, Grosan, Crina, Pedrycz, Witold

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Researcher 2 20%
Student > Doctoral Student 1 10%
Student > Ph. D. Student 1 10%
Unknown 3 30%
Readers by discipline Count As %
Engineering 5 50%
Computer Science 2 20%
Unknown 3 30%