Computational Intelligence An Introduction

ISBN-10: 0470035617

ISBN-13: 9780470035610

Edition: 2nd 2007

List price: $118.00 Buy it from $71.85
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Description:

The main focus of the book is on computational modelling of biological and natural intelligent systems in order to develop nature inspired artificially intelligent systems. These algorithmic models have as their main objective to facilitate the implementation of artificial intelligent systems for solving complex real-world systems (e.g. fuzzy systems are applied successfully to control systems, gear transmission, breaking systems; swarm intelligence to image classification). This second edition expands on all these paradigms, providing a more detailed and equal treatment of them all. Most recent advances in CI have been added, namely artificial immune systems, hybrid systems, and a section on how to perform empirical studies.
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Book details

List price: $118.00
Edition: 2nd
Copyright year: 2007
Publisher: John Wiley & Sons, Incorporated
Publication date: 11/19/2007
Binding: Hardcover
Pages: 628
Size: 6.93" wide x 9.92" long x 1.48" tall
Weight: 2.684
Language: English

Figures
Tables
Algorithms
Preface
Introduction
Introduction to Computational Intelligence
Computational Intelligence Paradigms
Short History
Assignments
Artificial Neural Networks
The Artificial Neuron
Calculating the Net Input Signal
Activation Functions
Artificial Neuron Geometry
Artificial Neuron Learning
Assignments
Supervised Learning Neural Networks
Neural Network Types
Supervised Learning Rules
Functioning of Hidden Units
Ensemble Neural Networks
Assignments
Unsupervised Learning Neural Networks
Background
Hebbian Learning Rule
Principal Component Learning Rule
Learning Vector Quantizer-I
Self-Organizing Feature Maps
Assignments
Radial Basis Function Networks
Learning Vector Quantizer-II
Radial Basis Function Neural Networks
Assignments
Reinforcement Learning
Learning through Awards
Model-Free Reinforcement LearningModel
Neural Networks and Reinforcement Learning
Assignments
Performance Issues (Supervised Learning)
PerformanceMeasures
Analysis of Performance
Performance Factors
Assignments
Evolutionary Computation
Introduction to Evolutionary Computation
Generic Evolutionary Algorithm
Representation - The Chromosome
Initial Population
Fitness Function
Selection
Reproduction Operators
Stopping Conditions
Evolutionary Computation versus Classical Optimization
Assignments
Genetic Algorithms
Canonical Genetic Algorithm
Crossover
Mutation
Control Parameters
Genetic Algorithm Variants
Advanced Topics
Applications
Assignments
Genetic Programming
Tree-Based Representation
Initial Population
Fitness Function
Crossover Operators
Mutation Operators
Building Block Genetic Programming
Applications
Assignments
Evolutionary Programming
Basic Evolutionary Programming
Evolutionary Programming Operators
Strategy Parameters
Evolutionary Programming Implementations
Advanced Topics
Applications
Assignments
Evolution Strategies
(1+1)-ES
Generic Evolution Strategy Algorithm
Strategy Parameters and Self-Adaptation
Evolution Strategy Operators
Evolution Strategy Variants
Advanced Topics
Applications of Evolution Strategies
Assignments
Differential Evolution
Basic Differential Evolution
DE/x/y/z
Variations to Basic Differential Evolution
Differential Evolution for Discrete-Valued Problems
Advanced Topics
Applications
Assignments
Cultural Algorithms
Culture and Artificial Culture
Basic Cultural Algorithm
Belief Space
Fuzzy Cultural Algorithm
Advanced Topics
Applications
Assignments
Coevolution
Coevolution Types
Competitive Coevolution
Cooperative Coevolution
Assignments
Computational Swarm Intelligence
Particle Swarm Optimization
Basic Particle Swarm Optimization
Social Network Structures
Basic Variations
Basic PSO Parameters
Single-Solution Particle SwarmOptimization
Advanced Topics
Applications
Assignments
Ant Algorithms
Ant Colony OptimizationMeta-Heuristic
Cemetery Organization and Brood Care
Division of Labor
Advanced Topics
Applications
Assignments
Artificial Immune Systems
Natural Immune System
Classical View
Antibodies and Antigens
TheWhite Cells
Immunity Types
Learning the Antigen Structure
The Network Theory
The Danger Theory
Assignments
Artificial Immune Models
Artificial Immune System Algorithm
Classical ViewModels
Clonal Selection TheoryModels
Network TheoryModels
Danger TheoryModels
Applications and Other AIS models
Assignments
Fuzzy Systems
Fuzzy Sets
Formal Definitions
Membership Functions
Fuzzy Operators
Fuzzy Set Characteristics
Fuzziness and Probability
Assignments
Fuzzy Logic and Reasoning
Fuzzy Logic
Fuzzy Inferencing
Assignments
Fuzzy Controllers
Components of Fuzzy Controllers
Fuzzy Controller Types
Assignments
Rough Sets
Concept of Discernibility
Vagueness in Rough Sets
Uncertainty in Rough Sets
Assignments
References
Optimization Theory
Basic Ingredients of Optimization Problems
Optimization ProblemClassifications
Optima Types
OptimizationMethod Classes
Unconstrained Optimization
Constrained Optimization
Multi-Solution Problems
Multi-Objective Optimization
Dynamic Optimization Problems
Index
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