Nazmul Siddique, Hojjat Adeli

Computational Intelligence (eBook, PDF)

Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing

• Format: PDF

Produktbeschreibung

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: * Covers all the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB® exercises and applications in each chapter * Presents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systems * Considers real world problems in the domain of systems modelling, control and optimization * Contains a foreword written by Lotfi Zadeh Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing is an ideal text for final year undergraduate, postgraduate and research students in electrical, control, computer, industrial and manufacturing engineering.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 536
• Erscheinungstermin: 22. März 2013
• Englisch
• ISBN-13: 9781118534809
• Artikelnr.: 38047040

Autorenporträt

Nazmul Siddique is a lecturer in the School of Computing and Intelligent Systems at the University of Ulster. He has published over 120 scientific research papers in journals and conferences including seven book chapters and two books. He is a senior member of the IEEE and has been involved in organising many international conferences. He is on the editorial board of the International Journal of Neural Systems, International Journal of Automation and Control Engineering, Journal of Behavioural Robotics, and Engineering Letters. Hojjat Adeli is the holder of Abba G. Lichtenstein Professorship at The Ohio State University (OSU). He is the Editor-in-Chief of three journals: Computer-Aided Civil and Infrastructure Engineering, Integrated Computer-Aided Engineering, and International Journal of Neural Systems. He has authored over 500 publications including 14 books and has won numerous awards. He is a Distinguished Member of ASCE, a Fellow of AAAS and IEEE. In April 2010 he was profiled as an engineering legend in the journal Leadership and Management in Engineering.

Inhaltsangabe

Foreword xiii Preface xv Acknowledgements xix 1 Introduction to
Computational Intelligence 1 1.1 Computational Intelligence 1 1.2 Paradigms
of Computational Intelligence 2 1.3 Approaches to Computational
Intelligence 3 1.4 Synergies of Computational Intelligence Techniques 11
1.5 Applications of Computational Intelligence 12 1.6 Grand Challenges of
Computational Intelligence 13 1.7 Overview of the Book 13 1.8 MATLAB R _
Basics 14 References 15 2 Introduction to Fuzzy Logic 19 2.1 Introduction
19 2.2 Fuzzy Logic 20 2.3 Fuzzy Sets 21 2.4 Membership Functions 22 2.5
Features of MFs 27 2.6 Operations on Fuzzy Sets 29 2.7 Linguistic Variables
33 2.8 Linguistic Hedges 35 2.9 Fuzzy Relations 37 2.10 Fuzzy If-Then Rules
39 2.11 Fuzzification 43 2.12 Defuzzification 44 2.13 Inference Mechanism
48 2.14 Worked Examples 54 2.15 MATLAB R _ Programs 61 References 61 3
Fuzzy Systems and Applications 65 3.1 Introduction 65 3.2 Fuzzy System 66
3.3 Fuzzy Modelling 67 3.4 Fuzzy Control 75 3.5 Design of Fuzzy Controller
81 3.6 Modular Fuzzy Controller 97 3.7 MATLAB R _ Programs 99 References
100 4 Neural Networks 103 4.1 Introduction 103 4.2 Artificial Neuron Model
106 4.3 Activation Functions 107 4.4 Network Architecture 108 4.5 Learning
in Neural Networks 124 4.6 Recurrent Neural Networks 149 4.7 MATLAB R _
Programs 155 References 156 5 Neural Systems and Applications 159 5.1
Introduction 159 5.2 System Identification and Control 160 5.3 Neural
Networks for Control 163 5.4 MATLAB R _ Programs 179 References 180 6
Evolutionary Computing 183 6.1 Introduction 183 6.2 Evolutionary Computing
183 6.3 Terminologies of Evolutionary Computing 185 6.4 Genetic Operators
194 6.5 Performance Measures of EA 208 6.6 Evolutionary Algorithms 209 6.7
MATLAB R _ Programs 234 References 235 7 Evolutionary Systems 239 7.1
Introduction 239 7.2 Multi-objective Optimization 243 7.3 Co-evolution 250
7.4 Parallel Evolutionary Algorithm 256 References 262 8 Evolutionary Fuzzy
Systems 265 8.1 Introduction 265 8.2 Evolutionary Adaptive Fuzzy Systems
267 8.3 Objective Functions and Evaluation 287 8.4 Fuzzy Adaptive
Evolutionary Algorithms 290 References 303 9 Evolutionary Neural Networks
307 9.1 Introduction 307 9.2 Supportive Combinations 309 9.3 Collaborative
Combinations 318 9.4 Amalgamated Combination 343 9.5 Competing Conventions
345 References 351 10 Neural Fuzzy Systems 357 10.1 Introduction 357 10.2
Combination of Neural and Fuzzy Systems 359 10.3 Cooperative Neuro-Fuzzy
Systems 360 10.4 Concurrent Neuro-Fuzzy Systems 369 10.5 Hybrid Neuro-Fuzzy
Systems 369 10.6 Adaptive Neuro-Fuzzy System 404 10.7 Fuzzy Neurons 409
10.8 MATLAB R _ Programs 411 References 412 Appendix A: MATLAB R _ Basics
415 Appendix B: MATLAB R _ Programs for Fuzzy Logic 433 Appendix C: MATLAB
R _ Programs for Fuzzy Systems 443 Appendix D: MATLAB R _ Programs for
Neural Systems 461 Appendix E: MATLAB R _ Programs for Neural Control
Design 473 Appendix F: MATLAB R _ Programs for Evolutionary Algorithms 489
Appendix G: MATLAB R _ Programs for Neuro-Fuzzy Systems 497 Index 507