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

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 chapterPresents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systemsConsiders real world problems in the domain of systems modelling, control and optimizationContains a foreword written by Lotfi ZadehComputational 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.Content: Chapter 1 Introduction to Computational Intelligence (pages 1–17): Chapter 2 Introduction to Fuzzy Logic (pages 19–63): Chapter 3 Fuzzy Systems and Applications (pages 65–101): Chapter 4 Neural Networks (pages 103–157): Chapter 5 Neural Systems and Applications (pages 159–181): Chapter 6 Evolutionary Computing (pages 183–237): Chapter 7 Evolutionary Systems (pages 239–264): Chapter 8 Evolutionary Fuzzy Systems (pages 265–305): Chapter 9 Evolutionary Neural Networks (pages 307–355): Chapter 10 Neural Fuzzy Systems (pages 357–414):