
Genetic Algorithms for Pattern Recognition
CRC Press
1st Edition
Published on 25. January 2019
Book
Paperback/Softback
336 pages
978-1-138-55888-5 (ISBN)
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.
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.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 18 mm
Weight
515 gr
ISBN-13
978-1-138-55888-5 (9781138558885)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Sankar K. Pal | Paul P. Wang
Genetic Algorithms for Pattern Recognition
E-Book
11/2017
CRC Press
€86.99
Available for download

Sankar K. Pal | Paul P. Wang
Genetic Algorithms for Pattern Recognition
E-Book
11/2017
CRC Press
€86.99
Available for download

Sankar K. Pal | Paul P. Wang
Genetic Algorithms for Pattern Recognition
Book
09/2017
1st Edition
CRC Press
€315.40
Shipment within 10-20 days
Persons
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
Content
1.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.