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Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing

Book Description

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.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. Foreword
  6. Preface
  7. Acknowledgements
  8. Chapter 1: Introduction to Computational Intelligence
    1. 1.1 Computational Intelligence
    2. 1.2 Paradigms of Computational Intelligence
    3. 1.3 Approaches to Computational Intelligence
    4. 1.4 Synergies of Computational Intelligence Techniques
    5. 1.5 Applications of Computational Intelligence
    6. 1.6 Grand Challenges of Computational Intelligence
    7. 1.7 Overview of the Book
    8. 1.8 MATLAB® Basics
    9. References
  9. Chapter 2: Introduction to Fuzzy Logic
    1. 2.1 Introduction
    2. 2.2 Fuzzy Logic
    3. 2.3 Fuzzy Sets
    4. 2.4 Membership Functions
    5. 2.5 Features of MFs
    6. 2.6 Operations on Fuzzy Sets
    7. 2.7 Linguistic Variables
    8. 2.8 Linguistic Hedges
    9. 2.9 Fuzzy Relations
    10. 2.10 Fuzzy If–Then Rules
    11. 2.11 Fuzzification
    12. 2.12 Defuzzification
    13. 2.13 Inference Mechanism
    14. 2.14 Worked Examples
    15. 2.15 MATLAB® Programs
    16. References
  10. Chapter 3: Fuzzy Systems and Applications
    1. 3.1 Introduction
    2. 3.2 Fuzzy System
    3. 3.3 Fuzzy Modelling
    4. 3.4 Fuzzy Control
    5. 3.5 Design of Fuzzy Controller
    6. 3.6 Modular Fuzzy Controller
    7. 3.7 MATLAB® Programs
    8. References
  11. Chapter 4: Neural Networks
    1. 4.1 Introduction
    2. 4.2 Artificial Neuron Model
    3. 4.3 Activation Functions
    4. 4.4 Network Architecture
    5. 4.5 Learning in Neural Networks
    6. 4.6 Recurrent Neural Networks
    7. 4.7 MATLAB® Programs
    8. References
  12. Chapter 5: Neural Systems and Applications
    1. 5.1 Introduction
    2. 5.2 System Identification and Control
    3. 5.3 Neural Networks for Control
    4. 5.4 MATLAB® Programs
    5. References
  13. Chapter 6: Evolutionary Computing
    1. 6.1 Introduction
    2. 6.2 Evolutionary Computing
    3. 6.3 Terminologies of Evolutionary Computing
    4. 6.4 Genetic Operators
    5. 6.5 Performance Measures of EA
    6. 6.6 Evolutionary Algorithms
    7. 6.7 MATLAB® Programs
    8. References
  14. Chapter 7: Evolutionary Systems
    1. 7.1 Introduction
    2. 7.2 Multi-objective Optimization
    3. 7.3 Co-evolution
    4. 7.4 Parallel Evolutionary Algorithm
    5. References
  15. Chapter 8: Evolutionary Fuzzy Systems
    1. 8.1 Introduction
    2. 8.2 Evolutionary Adaptive Fuzzy Systems
    3. 8.3 Objective Functions and Evaluation
    4. 8.4 Fuzzy Adaptive Evolutionary Algorithms
    5. References
  16. Chapter 9: Evolutionary Neural Networks
    1. 9.1 Introduction
    2. 9.2 Supportive Combinations
    3. 9.3 Collaborative Combinations
    4. 9.4 Amalgamated Combination
    5. 9.5 Competing Conventions
    6. References
  17. Chapter 10: Neural Fuzzy Systems
    1. 10.1 Introduction
    2. 10.2 Combination of Neural and Fuzzy Systems
    3. 10.3 Cooperative Neuro-Fuzzy Systems
    4. 10.4 Concurrent Neuro-Fuzzy Systems
    5. 10.5 Hybrid Neuro-Fuzzy Systems
    6. 10.6 Adaptive Neuro-Fuzzy System
    7. 10.7 Fuzzy Neurons
    8. 10.8 MATLAB® Programs
    9. References
  18. Appendix A: MATLAB® Basics
  19. Appendix B: MATLAB® Programs for Fuzzy Logic
  20. Appendix C: MATLAB® Programs for Fuzzy Systems
  21. Appendix D: MATLAB® Programs for Neural Systems
  22. Appendix E: MATLAB® Programs for Neural Control Design
  23. Appendix F: MATLAB® Programs for Evolutionary Algorithms
  24. Appendix G: MATLAB® Programs for Neuro-Fuzzy Systems
  25. Index