![](/images/graphics-bg.png)
A Comparison of Evolutionary Computation Techniques for IIR Model Identification
Joint Authors
Zaldivar, Daniel
Cuevas, Erik
Gálvez, Jorge
Hinojosa, Salvador
Avalos, Omar
Pérez-Cisneros, Marco
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-12-25
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
System identification is a complex optimization problem which has recently attracted the attention in the field of science and engineering.
In particular, the use of infinite impulse response (IIR) models for identification is preferred over their equivalent FIR (finite impulse response) models since the former yield more accurate models of physical plants for real world applications.
However, IIR structures tend to produce multimodal error surfaces whose cost functions are significantly difficult to minimize.
Evolutionary computation techniques (ECT) are used to estimate the solution to complex optimization problems.
They are often designed to meet the requirements of particular problems because no single optimization algorithm can solve all problems competitively.
Therefore, when new algorithms are proposed, their relative efficacies must be appropriately evaluated.
Several comparisons among ECT have been reported in the literature.
Nevertheless, they suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments.
This study presents the comparison of various evolutionary computation optimization techniques applied to IIR model identification.
Results over several models are presented and statistically validated.
American Psychological Association (APA)
Cuevas, Erik& Gálvez, Jorge& Hinojosa, Salvador& Avalos, Omar& Zaldivar, Daniel& Pérez-Cisneros, Marco. 2014. A Comparison of Evolutionary Computation Techniques for IIR Model Identification. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1039772
Modern Language Association (MLA)
Cuevas, Erik…[et al.]. A Comparison of Evolutionary Computation Techniques for IIR Model Identification. Journal of Applied Mathematics No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1039772
American Medical Association (AMA)
Cuevas, Erik& Gálvez, Jorge& Hinojosa, Salvador& Avalos, Omar& Zaldivar, Daniel& Pérez-Cisneros, Marco. A Comparison of Evolutionary Computation Techniques for IIR Model Identification. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1039772
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1039772