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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
Attention for Chapter 3: Genetically Optimized Self-organizing Neural Networks Based on Polynomial and Fuzzy Polynomial Neurons: Analysis and Design
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