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

Yu Cheng*, Lan Wang, Jinglu Hu

*この研究の対応する著者

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings
ページ613-618
ページ数6
DOI
出版ステータスPublished - 2009
イベント2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Coimbatore, India
継続期間: 2009 12 92009 12 11

出版物シリーズ

名前2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings

Conference

Conference2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009
国/地域India
CityCoimbatore
Period09/12/909/12/11

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ サイエンスの応用
  • ソフトウェア

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