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OverviewSolving pattern recognition problems involves an enormous amount of computational effort. By applying genetic algorithms - a computational method based on the way chromosomes in DNA recombine - these problems are more efficiently and more accurately solved. Genetic Algorithms for Pattern Recognition covers a broad range of applications in science and technology, describing the integration of genetic algorithms in pattern recognition and machine learning problems to build intelligent recognition systems. The articles, written by leading experts from around the world, accomplish several objectives: they provide insight into the theory of genetic algorithms; they develop pattern recognition theory in light of genetic algorithms; and they illustrate applications in artificial neural networks and fuzzy logic. The cross-sectional view of current research presented in Genetic Algorithms for Pattern Recognition makes it a unique text, ideal for graduate students and researchers. Full Product DetailsAuthor: Sankar K. Pal (Indian Statistical Institute, Calcutta, India Indian Statistical Institute Indian Statistical Institute, Kolkata, India) , Paul P. Wang (Duke University, Durham, North Carolina, USA) , Paul P. Wang (Duke University, Durham, North Carolina, USA) , Sanghamitra Bandyopadhyay (Indian Statistical Institute, Calcutta, India Indian Statistical Institute Indian Statistical Institute, Kolkata, India)Publisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.453kg ISBN: 9781138105577ISBN 10: 1138105570 Pages: 336 Publication Date: 20 September 2017 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1.Fitness Evaluation in Genetic Algorithms with Ancestors' Influence 2. The Walsh Transform and the Theory of the Simple Genetic Algorithm 3. Adaptation in Genetic Algorithms 4. An Empirical Evaluation of Genetic Algorithms on Noisy Objective Functions 5. Generalization of Heuristics Learned in Genetics-Based Learning 6. Genetic Algorithm-Based Pattern Classification: Relationship with Bayes Classifier 7. Genetic Algorithms and Recognition Problems 8. Mesoscale Feature Labeling from Satellite Images 9. Learning to Learn with Evolutionary Growth Perceptrons 10. Genetic Programming of Logic-Based Neural Networks 11. Construction of Fuzzy Classification Systems with Linguistic If-Then Rules Using Genetic Algorithms 12. A Genetic Algorithm Method for Optimizing the Fuzzy Component of a Fuzzy Decision Tree 13. Genetic Design of Fuzzy Controllers. Index.ReviewsAuthor InformationSankar K. Pal, Paul P. Wang Tab Content 6Author Website:Countries AvailableAll regions |