Overview

This is an organized edited collection of contributed chapters covering basic principles, methodologies, and applications of fuzzy systems, neural networks and genetic algorithms. All chapters are original contributions by leading researchers written exclusively for this volume. The book reviews important concepts and models, and focuses on specific methodologies common to fuzzy systems, neural networks and evolutionary computation. The emphasis is on development of cooperative models of hybrid systems. Included are applications related to intelligent data analysis, process analysis, intelligent adaptive information systems, systems identification, nonlinear systems, power and water system design, and many others. The book aims to provide researchers and engineers with up-to-date coverage of new results, methodologies and applications for building intelligent systems capable of solving large-scale problems.

Full Product Details

Author:   Da Ruan
Publisher:   Springer
Imprint:   Springer
Edition:   1997 ed.
Dimensions:   Width: 15.50cm , Height: 2.20cm , Length: 23.50cm
Weight:   1.570kg
ISBN:  

9780792399995

ISBN 10:   0792399994
Pages:   354
Publication Date:   30 September 1997
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1: Basic Principles and Methodologies.- 1 Introduction to Fuzzy Systems, Neural Networks, and Genetic Algorithms.- 2 A Fuzzy Neural Network for Approximate Fuzzy Reasoning.- 3 Novel Neural Algorithms for Solving Fuzzy Relation Equations.- 4 Methods for Simplification of Fuzzy Models.- 5 A New Approach of Neurofuzzy Learning Algorithm.- 2: Data Analysis and Information Systems.- 6 Neural Networks in Intelligent Data Analysis.- 7 Data-Driven Identification of Key Variables.- 8 Applications of Intelligent Techniques in Process Analysis.- 9 Neurofuzzy-Chaos Engineering for Building Intelligent Adaptive Information Systems.- 10 A Sequential Training Strategy for Locally Recurrent Neural Networks.- 3: Nonlinear Systems and System Identification.- 11 Adaptive Genetic Programming for System Identification.- 12 Nonlinear System Identification with Neurofuzzy Methods.- 13 A Genetic Algorithm for Mixed-Integer Optimisation in Power and Water System Design and Control.- 14 Soft Computing Based Signal Prediction, Restoration, and Filtering.

Reviews

Overall Intelligent Hybrid Systems is an extemely useful book. It is absolutely essential for anyone attempting to keep with recent developments in soft computing, and in some contexts it may serve as an introductory guide.' International Journal General Systems, 29: 2

'Overall Intelligent Hybrid Systems is an extemely useful book. It is absolutely essential for anyone attempting to keep with recent developments in soft computing, and in some contexts it may serve as an introductory guide.' International Journal General Systems, 29:2

'Overall Intelligent Hybrid Systems is an extemely useful book. It is absolutely essential for anyone attempting to keep with recent developments in soft computing, and in some contexts it may serve as an introductory guide.' International Journal General Systems, 29:2

'Overall Intelligent Hybrid Systems is an extemely useful book. It is absolutely essential for anyone attempting to keep with recent developments in soft computing, and in some contexts it may serve as an introductory guide.' International Journal General Systems, 29:2

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