Please use this identifier to cite or link to this item: https://idr.l3.nitk.ac.in/jspui/handle/123456789/13797
Title: Evolutionary computing approaches to system identification
Authors: Subudhi B.
Jena D.
Issue Date: 2016
Citation: Handbook of Research on Computational Intelligence Applications in Bioinformatics, 2016, Vol., pp.329-368
Abstract: In this chapter, we describe an important class of engineering problem called system identification which is an essential requirement for obtaining models of system of concern that would be necessary for controlling, analyzing the systems. The system identification problem is essentially to pick up the best model out of the several candidate models. Thus, the problem of system identification or modeling building turns out to be an optimization problem. The chapter explain what are different evolutionary computing techniques used in the past and the state- of the art technologies on evolutionary computation. Then, some case studies have been included how the system identification of a number of complex systems effectively achieved by employing these evolutionary computing techniques. © 2016 by IGI Global. All rights reserved.
URI: 10.4018/978-1-5225-0427-6.ch015
http://idr.nitk.ac.in/jspui/handle/123456789/13797
Appears in Collections:3. Book Chapters

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