Kriging surrogate model enhanced by coordinate transformation of design space based on eigenvalue decomposition

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

The Kriging surrogate model, which is frequently employed to apply evolutionary computation to real-world problems, with coordinate transformation of design space is proposed to improve the approximation accuracy of objective functions with correlated design variables. Eigenvalue decomposition is used to extract significant trends in the objective function from its gradients and identify suitable coordinates. Comparing with the ordinary Kriging model, the proposed method shows higher accuracy in the approximation of twodimensional test functions and reduces the computational cost to achieve the global optimization. In the application to an airfoil design problem with spline curves as correlated design variables, the proposed method achieves better performances not only in the approximation accuracy but also the ability to explore the optimal solution.

本文言語English
ホスト出版物のタイトルEvolutionary Multi-Criterion Optimization - 8th International Conference, EMO 2015, Proceedings
編集者António Gaspar-Cunha, Carlos Henggeler Antunes, Carlos A. Coello Coello
出版社Springer-Verlag
ページ321-335
ページ数15
ISBN(電子版)9783319159331
DOI
出版ステータスPublished - 2015 1 1
イベント8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 - Guimarães, Portugal
継続期間: 2015 3 292015 4 1

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9018
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015
国/地域Portugal
CityGuimarães
Period15/3/2915/4/1

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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