2011 Fourth International Joint Conference on Computational Sciences and Optimization 2011
DOI: 10.1109/cso.2011.56
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A Sequential Optimization Method Based on Kriging Surrogate Model

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Cited by 6 publications
(5 citation statements)
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“…where y l is the lth set of the Y vector of the Kriging surrogate model, y l is the lth component of the superharmonic component amplitudes calculated by finite element analysis, y is the mean of the true values, and q is the length of the vector y l . is paper adopts the multipoint adding strategy to update the Kriging surrogate model if the predicted superharmonic components amplitudes cannot meet SC and EISE [41].…”
Section: Construction Of the Kriging Surrogate Modelmentioning
confidence: 99%
“…where y l is the lth set of the Y vector of the Kriging surrogate model, y l is the lth component of the superharmonic component amplitudes calculated by finite element analysis, y is the mean of the true values, and q is the length of the vector y l . is paper adopts the multipoint adding strategy to update the Kriging surrogate model if the predicted superharmonic components amplitudes cannot meet SC and EISE [41].…”
Section: Construction Of the Kriging Surrogate Modelmentioning
confidence: 99%
“…Gao et al [12] pointed out that the two-layer Kriging model can reduce uncertainty analysis, and then improved the computational efficiency. Through cross-validation, Dellino et al [6] proved that two-layer Kriging model has smaller relative prediction errors than one-layer Kriging model.…”
Section: B Two-layer Kriging Modelmentioning
confidence: 99%
“…Step 5: Use the following formulas to estimate the means and the standard deviations of the cost C for different quantity Q : Step 6: Formulate one Kriging model for 30 = Q N estimated means according to (11); and another Kriging model for 30 = Q N estimated standard deviations according to (12). The two Kriging model resulting from Step 6 and the true functions are displayed in Fig.…”
Section: Eoq Model Optimizationmentioning
confidence: 99%
“…The additional points for rebuilding the Kriging model are selected by the possibility of existing in this region. According to the previous works, 17,20 in order to set the convergence tolerance e without considering the magnitudes of responses, the convergence criterion is chosen as…”
Section: Kriging Modelmentioning
confidence: 99%
“…Kriging approximation is widely applied as an efficient and accuracy method and makes it possible for reliability analysis. 9,[16][17][18][19][20] In the optimization process, parameterization provides a rapid and automated manipulation of the analysis model. A high-quality parameterization has two conflicting objects: (1) ensure a bigger design space and (2) avoid any failure in establishing model.…”
Section: Introductionmentioning
confidence: 99%