๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Genetic Algorithms for Control and Signal Processing

โœ Scribed by Kim F. Man, Kit S. Tang, Sam Kwong, Wolfgang A. Halang (auth.)


Publisher
Springer-Verlag London
Year
1997
Tongue
English
Leaves
225
Series
Advances in Industrial Control
Edition
1
Category
Library

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โœฆ Synopsis


The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, . . . , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The emerging technologies in control include fuzzy logic, intelligent control, neural networks and hardware developments like micro-electro-mechanical systems and autonomous vehicles. This volume describes the biological background, basic construction and application of the emerging technology of Genetic Algorithms. Dr Kim Man and his colleagues have written a book which is both a primer introducing the basic concepts and a research text which describes some of the more advanced applications of the genetic algorithmic method. The applications described are especially useful since they indicate the power of the GA method in solving a wide range of problems. These sections are also instructive in showing how the mechanics of the GA solutions are obtained thereby acting as a template for similar types of problems. The volume is a very welcome contribution to the Advances in Industrial Control Series. M. J. Grimble and M. A.

โœฆ Table of Contents


Front Matter....Pages i-xx
Introduction Background and Biological Inspiration....Pages 1-20
Modification in Genetic Algorithm....Pages 21-29
Intrinsic Characteristics....Pages 31-48
Advanced GA Applications....Pages 49-112
Hierarchical Genetic Algorithm....Pages 113-122
Filtering Optimization....Pages 123-148
Emerging Technology....Pages 149-186
Back Matter....Pages 187-211

โœฆ Subjects


Control


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