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Evolutionary Computing Approaches to System Identification

Evolutionary Computing Approaches to System Identification

Bidyadhar Subudhi, Debashisha Jena
Copyright: © 2016 |Pages: 40
ISBN13: 9781522504276|ISBN10: 1522504273|EISBN13: 9781522504283
DOI: 10.4018/978-1-5225-0427-6.ch015
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MLA

Subudhi, Bidyadhar, and Debashisha Jena. "Evolutionary Computing Approaches to System Identification." Handbook of Research on Computational Intelligence Applications in Bioinformatics, edited by Sujata Dash and Bidyadhar Subudhi, IGI Global, 2016, pp. 329-368. https://doi.org/10.4018/978-1-5225-0427-6.ch015

APA

Subudhi, B. & Jena, D. (2016). Evolutionary Computing Approaches to System Identification. In S. Dash & B. Subudhi (Eds.), Handbook of Research on Computational Intelligence Applications in Bioinformatics (pp. 329-368). IGI Global. https://doi.org/10.4018/978-1-5225-0427-6.ch015

Chicago

Subudhi, Bidyadhar, and Debashisha Jena. "Evolutionary Computing Approaches to System Identification." In Handbook of Research on Computational Intelligence Applications in Bioinformatics, edited by Sujata Dash and Bidyadhar Subudhi, 329-368. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0427-6.ch015

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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.

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