1st Edition

Revival: Genetic Algorithms for Pattern Recognition (1986)

ISBN 9781138558885
Published January 25, 2019 by CRC Press
336 Pages

USD $69.95

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Book 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

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Sankar Kumar Pal is a Distinguished Scientist and former Director of the Indian Statistical Institute, Kolkata, India. He is a computer scientist with an international reputation on fuzzy neural network, soft computing, and machine intelligence. He founded the Machine Intelligence Unit in 1993, and the Center for Soft Computing Research: A National Facility in 2004, both at the ISI. He is the founder President of the Indian National Academy of Engineering, Kolkata Chapter