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An efficient algorithm for Kriging approximation and optimization with large-scale sampling data

delete2004-01-01
delete65
PRE
AI
S
Sei-ichiro SAKATA *
F
Fumihiro ASHIDA
M
Masahiro Zako
DOI：10.1016/j.cma.2003.10.006delete
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Abstract

Abstract

En 中文
This paper describes an algorithm to improve a computational cost for estimation using the Kriging method with a large number of sampling data. An improved formula to compute the weighting coefficient for Kriging estimation is proposed. The Sherman-Morrison-Woodbury formula is applied to solving an approximated simultaneous equation to determine a weighting coefficient. A profile of the matrix is reduced by sorting of given data. Applying the proposal formula to several examples indicates its characteristics. As a numerical example, layout optimisation of a beam structure for eigenfrequency maximization is solved. The results show an applicability and effectiveness of the proposed method. (C) 2003 Elsevier B.V. All rights reserved.
Keywords:
Kriging estimation
Sherman-Morrison-Woodbury formula
computational cost
structural optimization
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Journal

Computer Methods in Applied Mechanics and Engineering cover
Computer Methods in Applied Mechanics and Engineering
IF:
7.3
Papers:
1.3W
Citations:
5.6W

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