A two-step method for nonlinear polynomial model identification based on evolutionary optimization

Yu Cheng, Lan Wang, Takayuki Furuzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

A two-step identification method for nonlinear polynomial model using Evolutionary Algorithm (EA) is proposed in this paper, and the method has the ability to select a parsimonious structure from a very large pool of model terms. In a nonlinear polynomial model, the number of candidate monomial terms increases drastically as the order of polynomial model increases, and it is impossible to obtain the accurate model structure directly even with state-of-art algorithms. The proposed method firstly carries out a pre-screening process to select a reasonable number of important monomial terms based on the importance index. In the next step, EA is applied to determine a set of significant terms to be included in the polynomial model. In this way, the whole identification algorithm is implemented very efficiently. Numerical simulations are carried out to demonstrate the effectiveness of the proposed identification method.

Original languageEnglish
Title of host publication2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings
Pages613-618
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Coimbatore
Duration: 2009 Dec 92009 Dec 11

Other

Other2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009
CityCoimbatore
Period09/12/909/12/11

Fingerprint

Evolutionary algorithms
Model structures
Screening
Statistical Models
Computer simulation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Software

Cite this

Cheng, Y., Wang, L., & Furuzuki, T. (2009). A two-step method for nonlinear polynomial model identification based on evolutionary optimization. In 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings (pp. 613-618). [5393428] https://doi.org/10.1109/NABIC.2009.5393428

A two-step method for nonlinear polynomial model identification based on evolutionary optimization. / Cheng, Yu; Wang, Lan; Furuzuki, Takayuki.

2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings. 2009. p. 613-618 5393428.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Cheng, Y, Wang, L & Furuzuki, T 2009, A two-step method for nonlinear polynomial model identification based on evolutionary optimization. in 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings., 5393428, pp. 613-618, 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009, Coimbatore, 09/12/9. https://doi.org/10.1109/NABIC.2009.5393428
Cheng Y, Wang L, Furuzuki T. A two-step method for nonlinear polynomial model identification based on evolutionary optimization. In 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings. 2009. p. 613-618. 5393428 https://doi.org/10.1109/NABIC.2009.5393428
Cheng, Yu ; Wang, Lan ; Furuzuki, Takayuki. / A two-step method for nonlinear polynomial model identification based on evolutionary optimization. 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings. 2009. pp. 613-618
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