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- Revival: Genetic Algorithms for Pattern Recognition (1986)
Revival: Genetic Algorithms for Pattern Recognition (1986)
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Product Details
Author:
Sankar K. Pal, Paul P. Wang
Format:
Paperback
Pages:
336
Publisher:
CRC Press (January 25, 2019)
Language:
English
Audience:
Professional and scholarly
ISBN-13:
9781138558885
Weight:
16oz
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_260403050944986-20260403.xml
Folder:
TAYLORFRANCIS
List Price:
$87.99
Series:
CRC Press Revivals
Case Pack:
1
As low as:
$83.59
Publisher Identifier:
P-CRC
Discount Code:
H
Country of Origin:
United States
Pub Discount:
30
Imprint:
CRC Press
Overview
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.
