Modified screening-based Kriging method with cross validation and application to engineering design

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In this paper, a basis screening Kriging method using cross validation error is proposed to alleviate computational burden of the dynamic Kriging while maintaining its accuracy. Metamodeling is widely used for design optimization of complex engineering applications where considerable computation time is required. The Kriging method is one of popular metamodeling methods due to its accuracy and efficiency. There have been many attempts to improve accuracy of the Kriging method, and the dynamic Kriging method using cross-validation error, which selects adequate basis functions to best describe the mean structure of a response using a genetic algorithm, achieves outstanding performance in terms of accuracy. However, despite its accuracy, the dynamic Kriging requires very large amounts of computation because of the genetic algorithm and no limitation for order of basis functions. In the proposed method, a basis function set is determined by screening each basis function instead of using the genetic algorithm, which has advantages in computation for high dimensional metamodels or repeated metamodel generation. Numerical studies with four mathematical examples and two engineering applications verify that the proposed basis screening Kriging significantly reduces computation time with similar accuracy as the dynamic Kriging.
Publisher
ELSEVIER SCIENCE INC
Issue Date
2019-06
Language
English
Article Type
Article
Citation

APPLIED MATHEMATICAL MODELLING, v.70, pp.626 - 642

ISSN
0307-904X
DOI
10.1016/j.apm.2019.01.030
URI
http://hdl.handle.net/10203/251756
Appears in Collection
ME-Journal Papers(저널논문)
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