Practical Applications of Computational Intelligence Techniques

1. Front Matter

   Pages i-xv

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2. An Introduction to Computational Intelligence Paradigms

   • A. Konar, L. C. Jain

   Pages 1-64

3. Networked Virtual Park

   • N. Magnenat-Thalmann, C. Joslin, U. Berner

   Pages 65-88

4. Commercial Coin Recognisers Using Neural and Fuzzy Techniques

   • J. M. Moreno, J. Madrenas, J. Cabestany

   Pages 89-120

5. Fuzzy Techniques in Intelligent Household Appliances

   • M. Mraz, N. Zimic, I. Lapanja, J. Virant, B. Skrt

   Pages 121-145

6. Neural Prediction in Industry: Increasing Reliability through Use of Confidence Measures and Model Combination

   • P. J. Edwards, G. Papadopoulos, A. F. Murray

   Pages 147-175

7. Handling the Back Calculation Problem in Aerial Spray Models Using a Genetic Algorithm

   • W. D. Potter, W. Bi, D. Twardus, H. Thistle, M. J. Twery, J. Ghent et al.

   Pages 177-222

8. Genetic Algorithm Optimization of a Filament Winding Process Modeled in WITNESS

   • E. Wilson, C.L. Karr, S. Messimer

   Pages 223-239

9. Genetic Algorithm for Optimizing the Gust Loads for Predicting Aircraft Loads and Dynamic Response

   • R. Mehrotra, C. L. Karr, T. A. Zeiler

   Pages 241-267

10. A Stochastic Dynamic Programming Technique for Property Market Timing

    • T. C. Chin, G. T. Mills

    Pages 269-298

11. A Hybrid Approach to Breast Cancer Diagnosis

    • M. Sordo, H. Buxton, D. Watson

    Pages 299-330

12. Artificial Neural Networks as a Computer Aid for Lung Disease Detection and Classification in Ventilation-Perfusion Lung Scans

    • G. D. Tourassi, E. D. Frederick, R. E. Coleman

    Pages 331-353

13. Neural Network for Classification of Focal Liver Lesions in Ultrasound Images

    • H. Yoshida

    Pages 355-378

14. Back Matter

    Pages 379-381

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Computational intelligence paradigms have attracted the growing interest of researchers, scientists, engineers and application engineers in a number of everyday applications. These applications are not limited to any particular field and include engineering, business, banking and consumer electronics. Computational intelligence paradigms include artificial intelligence, artificial neural networks, fuzzy systems and evolutionary computing. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimisation applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge.
Practical Applications of Computational Intelligence Techniques contains twelve chapters providing actual application of these techniques in the real world. Such examples include, but are not limited to, intelligent household appliances, aerial spray models, industrial applications and medical diagnostics and practice. This book will be useful to researchers, practicing engineers/scientists and students, who are interested in developing practical applications in a computational intelligence environment.

• algorithms
• artificial intelligence
• artificial neural network
• classification
• computational intelligence
• electronics
• evolution
• evolutionary computation
• fuzzy
• genetic algorithm
• genetic algorithms
• knowledge
• neural network
• optimization
• programming

• University of South Australia, Adelaide, Australia

  Lakhmi Jain

• University of London, London, UK

  Philippe Wilde

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