Genetic algorithms for pattern recognition
Author(s)
Bibliographic Information
Genetic algorithms for pattern recognition
CRC Press, c1996
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
Solving 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.
Table of Contents
Fitness Evaluation in Genetic Algorithms with Ancestors' Influence, S. De, A. Ghosh, and S.K. Pal
The Walsh Transform and the Theory of the Simple Genetic Algorithm, M.D. Vose and A.H. Wright
Adaptation in Genetic Algorithms, L.M. Patnaik and M. Srinivas
An Empirical Evaluation of Genetic Algorithms on Noisy Objective Functions, K. Mathias, D. Whitley, A. Kusuma, and C. Stork
Generalization of Heuristics Learned in Genetics-Based Learning, B.W. Wah, A. Ieumwananonthachai, and Y.-C. Li
Genetic Algorithm-Based Pattern Classification: Relationship with Bayes Classifier, C.A. Murthy, S. Bandyopadhyay, and S.K. Pal
Genetic Algorithms and Recognition Problems, H. Van Hove and A. Verschoren
Mesoscale Feature Labeling from Satellite Images, B.P. Buckles, F.E. Petry, D. Prabhu, and M. Lybanon
Learning to Learn with Evolutionary Growth Perceptrons, S.G. Romaniuk
Genetic Programming of Logic-Based Neural Networks, V.C. Gaudet
Construction of Fuzzy Classification Systems with Linguistic If-Then Rules Using Genetic Algorithms, H. Ishibuchik, T. Murata, and H. Tanaka
A Genetic Algorithm Method for Optimizing the Fuzzy Component of a Fuzzy Decision Tree, C.Z. Janikow
Genetic Design of Fuzzy Controllers, M.G. Cooper and J.J. Vidal
Index
by "Nielsen BookData"