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Soft computing and fractal theory for intelligent manufacturing

Soft computing and fractal theory for intelligent manufacturing

Material type
단행본
Personal Author
Castillo, Oscar, 1959- Melin, Patricia , 1962-
Title Statement
Soft computing and fractal theory for intelligent manufacturing / Oscar Castillo, Patricia Melin.
Publication, Distribution, etc
Heidelberg ;   New York :   Physica-Verlag,   2003.  
Physical Medium
xiv, 283 p. : ill. ; 24 cm.
Series Statement
Studies in fuzziness and soft computing ; v. 117
ISBN
3790815470 (alk. paper) :
Bibliography, Etc. Note
Includes bibliographical references and index.
Subject Added Entry-Topical Term
Soft computing. Fractals. Manufacturing processes.
000 00963camuu2200277 a 4500
001 000001094649
005 20030915154019
008 021125s2003 gw a b 001 0 eng
020 ▼a 3790815470 (alk. paper) : ▼c EUR 59.95
040 ▼a DLC ▼c DLC ▼d DLC ▼d 244002
042 ▼a pcc
049 0 ▼l 151148301
050 0 0 ▼a QA76.9.S63 ▼b C35 2003
082 0 0 ▼a 006.3 ▼2 21
090 ▼a 006.3 ▼b C353s
100 1 ▼a Castillo, Oscar, ▼d 1959-
245 1 0 ▼a Soft computing and fractal theory for intelligent manufacturing / ▼c Oscar Castillo, Patricia Melin.
260 ▼a Heidelberg ; ▼a New York : ▼b Physica-Verlag, ▼c 2003.
300 ▼a xiv, 283 p. : ▼b ill. ; ▼c 24 cm.
440 0 ▼a Studies in fuzziness and soft computing ; ▼v v. 117
504 ▼a Includes bibliographical references and index.
650 0 ▼a Soft computing.
650 0 ▼a Fractals.
650 0 ▼a Manufacturing processes.
700 1 ▼a Melin, Patricia , ▼d 1962-

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Sejong Academic Information Center/Science & Technology/ Call Number 006.3 C353s Accession No. 151148301 Availability Available Due Date Make a Reservation Service C

Contents information

Table of Contents

1 Introduction.- 2 Type-1 Fuzzy Logic.- 2.1 Type-1 Fuzzy Set Theory.- 2.2 Fuzzy Rules and Fuzzy Reasoning.- 2.2.1 Fuzzy Relations.- 2.2.2 Fuzzy Rules.- 2.3 Fuzzy Inference Systems.- 2.4 Fuzzy Modelling.- 2.5 Summary.- 3 Type-2 Fuzzy Logic.- 3.1 Type-2 Fuzzy Sets.- 3.2 Operations of Type-2 Fuzzy Sets.- 3.3 Type-2 Fuzzy Systems.- 3.3.1 Singleton Type-2 Fuzzy Logic Systems.- 3.3.2 Non-Singleton Fuzzy Logic Systems.- 3.3.3 Sugeno Type-2 Fuzzy Systems.- 3.4 Summary.- 4 Supervised Learning Neural Networks.- 4.1 Backpropagation for Feedforward Networks.- 4.1.1 The Backpropagation Learning Algorithm.- 4.1.2 Backpropagation Multilayer Perceptrons.- 4.1.3 Methods for Speeding up Backpropagation.- 4.2 Radial Basis Function Networks.- 4.3 Adaptive Neuro-Fuzzy Inference Systems.- 4.3.1 ANFIS Architecture.- 4.3.2 Learning Algorithm.- 4.4 Summary.- 5 Unsupervised Learning Neural Networks.- 5.1 Competitive Learning Networks.- 5.2 Kohonen Self-Organizing Networks.- 5.3 Learning Vector Quantization.- 5.4 The Hopfield Network.- 5.5 Summary.- 6 Genetic Algorithms and Simulated Annealing.- 6.1 Genetic Algorithms.- 6.2 Modifications to Genetic Algorithms.- 6.2.1 Chromosome Representation.- 6.2.2 Objective Function and Fitness.- 6.2.3 Selection Methods.- 6.2.4 Genetic Operations.- 6.2.5 Parallel Genetic Algorithm.- 6.3 Simulated Annealing.- 6.4 Applications of Genetic Algorithms.- 6.4.1 Evolving Neural Networks.- 6.4.1.1 Evolving Weights in a Fixed Network.- 6.4.1.2 Evolving Network Architectures.- 6.4.2 Evolving Fuzzy Systems.- 6.5 Summary.- 7 Dynamical Systems Theory.- 7.1 Basic Concepts of Dynamical Systems.- 7.2 Controlling Chaos.- 7.2.1 Controlling Chaos through Feedback.- 7.2.1.1 Ott-Grebogi-Yorke Method.- 7.2.1.2 Pyragas's Control Methods.- 7.2.1.3 Controlling Chaos by Chaos.- 7.2.2 Controlling Chaos without Feedback.- 7.2.2.1 Control through Operating Conditions.- 7.2.2.2 Control by System Design.- 7.2.2.3 Taming Chaos.- 7.2.3 Method Selection.- 7.3 Summary.- 8 Plant Monitoring and Diagnostics.- 8.1 Monitoring and Diagnosis.- 8.2 Fractal Dimension of a Geometrical Object.- 8.3 Fuzzy Estimation of the Fractal Dimension.- 8.4 Plant Monitoring with Fuzzy-Fractal Approach.- 8.5 Experimental Results.- 8.6 Summary.- 9 Adaptive Control of Non-Linear Plants.- 9.1 Fundamental Adaptive Fuzzy Control Concept.- 9.2 Basic Concepts of Stepping Motors.- 9.2.1 Variable Reluctance Motors.- 9.2.2 Unipolar Motors.- 9.2.3 Bipolar Motors.- 9.2.4 Dynamics of the Stepping Motor.- 9.2.5 Control of the Stepping Motor.- 9.3 Fuzzy Logic Controller of the Stepping Motor.- 9.4 Hardware Implementation of ANFIS.- 9.5 Experimental Results.- 9.6 Summary.- 10 Automated Quality Control in Sound Speaker Manufacturing.- 10.1 Introduction.- 10.2 Basic Concepts of Sound Speakers.- 10.2.1 Sound Basics.- 10.2.2 Making Sound.- 10.2.3 Chunks of the Frequency Range.- 10.2.4 Boxes of Sound.- 10.2.5 Alternative Speaker Designs.- 10.3 Description of the Problem.- 10.4 Fractal Dimension of a Sound Signal.- 10.5 Experimental Results.- 10.6 Summary.- 11 Intelligent Manufacturing of Television Sets.- 11.1 Introduction.- 11.2 Imaging System of the Television Set.- 11.2.1 The Cathode Ray Tube.- 11.2.2 Phosphor.- 11.2.3 The Black-and-White TV Signal.- 11.2.4 Adding Color.- 11.3 Breeder Genetic Algorithm for Optimization.- 11.3.1 Genetic Algorithm for Optimization.- 11.4 Automated Electrical Tuning of Television Sets.- 11.5 Intelligent System for Control.- 11.6 Simulation Results.- 11.7 Summary.- 12 Intelligent Manufacturing of Batteries.- 12.1 Intelligent Control of the Battery Charging Process.- 12.1.1 Problem Description.- 12.1.2 Fuzzy Method for Control.- 12.1.3 Neuro-Fuzzy Method for Control.- 12.1.4 Neuro-Fuzzy-Genetic Method for Control.- 12.2 Hardware Implementation of the Fuzzy Controller for the Charging Process.- 12.2.1 Introduction.- 12.2.2 Fuzzy Control.- 12.2.3 Implementation of the Fuzzy Controller.- 12.2.4 Experimental Results.- 12.3 Automated Quality Control of Batteries.- 1


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