|1/2010 - 17|
View TOC | « Previous Article | Next Article »
Elite Based Multiobjective Genetic Programming in Nonlinear Systems IdentificationPATELLI, A. , FERARIU, L.
|View the paper record and citations in|
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (427 KB) | Citation | Downloads: 1,358 | Views: 5,007|
evolutionary algorithms, genetic programming, multiobjective optimization, nonlinear system identification
programming(7), genetic(6), evolutionary(6), systems(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2010-02-27
Volume 10, Issue 1, Year 2010, On page(s): 94 - 99
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.01017
Web of Science Accession Number: 000275458900017
SCOPUS ID: 77954683610
The nonlinear systems identification method described in the paper is based on genetic programming, a robust tool, able to ensure the simultaneous selection of model structure and parameters. The assessment of potential solutions is done via a multiobjective approach, making use of both accuracy and parsimony criteria, in order to encourage the selection of accurate and compact models, characterized by expected good generalization capabilities. The evolutionary process is implemented from an elitist standpoint, and upgraded by means of two original contributions, namely an adaptive niching mechanism and an elite clustering procedure. The authors have also suggested a set of enhancements to aid the genetic operators in effectively exploring the space of possible model structures. In symbiosis with the customized genetic operators, a QR local optimization procedure was integrated within the algorithm. It exploits the nonlinear, linear in parameter form that the working models are generated in, for providing a faster parameter computation. The performances of the proposed methodology were revealed on two applications, of different complexity levels: the identification of a simulated nonlinear system and the identification of an industrial plant.
|References|||||Cited By «-- Click to see who has cited this paper|
| H. Wey, S. A. Billings, J. Lui, "Term and Variable Selection for Nonlinear Models", Int. J. Control 77, pp. 86-110, 2004
 N. Nedjah, A. Abraham, L. de Macedo Mourelle, "Genetic systems programming : theory and experiences", Springer, Netherlands, 2006 [PermaLink]
 P. J. Flemming, R. C. Purshouse, "Evolutionary Algorithms in Control Systems Engineering: A Survey", Control Engineering Practice 10, pp. 1223-1241, 2002
[CrossRef] [Web of Science Times Cited 369] [SCOPUS Times Cited 494]
 J. R. Koza, "Genetic Programming: On the Programming of Computers by Means of Natural Selection", Cambridge, MA, MIT Press, 1992, pp. 73-190 [PermaLink]
 J. Madar, J. Abonyi, F. Szeifert, "Genetic Programming for System Identification", 2005, Available: http://www.fmt.vein.hu/softcomp/isda04_gpolsnew.pdf
 R. Riolo, T. Soule, B. Worzel, "Genetic Programming Theory and Practice IV", Springer, USA, 2007
 K. Rodriguez-Vasquez, C. M. Fonseca, P. J. Flemming, "Identifying the Structure of Nonlinear Dynamic Systems Using Multiobjective Genetic Programming", IEEE Transactions on Systems Man and Cybernetics, Part A - Systems and Humans, 34, pp. 531-534, 2004
[CrossRef] [Web of Science Times Cited 74] [SCOPUS Times Cited 100]
 J. Knowles , D. Corne, K. Deb, "Multiobjective Problem Solving from Nature - From Concepts to Applications", Natural Computing Series, Springer, USA, 2008 [PermaLink]
 K. Deb, "Multiobjective Optimization using Evolutionary Algorithms", John Wiley and Sons, USA, 2001 [PermaLink]
 Y. G. Woldesenbet, G. C. Yen, "Dynamic Evolutionary Algorithm with Variable Relocation", IEEE Transactions on Evolutionary Computation, vol. 13, no. 3, pp. 500-513, 2009
[CrossRef] [Web of Science Times Cited 83] [SCOPUS Times Cited 98]
 L. Ferariu, A. Patelli, "Multi-objective Genetic Programming for Nonlinear System Identification", Proc. of ICANNGA09, Kuopio, Finland, 2009
 T. Back, D. Fogel, Z. Michalewicz, "Evolutionary Computation - Advanced Algorithms and Operators", Institute of Physics Publishing, 2000 [PermaLink]
 L. Ferariu, M. Voicu, "Nonlinear System Identification Based on Evolutionary Dynamic Neural Networks wih Hybrid Structure", Proc. of IFAC Congress, Prague, Czech Republic, 2005
Web of Science® Citations for all references: 526 TCR
SCOPUS® Citations for all references: 692 TCR
Web of Science® Average Citations per reference: 40 ACR
SCOPUS® Average Citations per reference: 53 ACR
TCR = Total Citations for References / ACR = Average Citations per Reference
We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more
Citations for references updated on 2023-06-04 07:58 in 25 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.