Showing results 1 to 6 of 6
Adaptive virtual support vector machine for reliability analysis of high-dimensional problems Song, Hyeongjin; Choi, K. K.; Lee, Ikjin; Zhao, Liang; Lamb, David, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.47, no.4, pp.479 - 491, 2013-04 |
Conservative Surrogate Model Using Weighted Kriging Variance for Sampling-Based RBDO Zhao, Liang; Choi, K. K.; Lee, Ikjin; Gorsich, David, JOURNAL OF MECHANICAL DESIGN, v.135, no.9, 2013-09 |
Metamodeling Method Using Dynamic Kriging for Design Optimization Zhao, Liang; Choi, K. K.; Lee, Ikjin, AIAA JOURNAL, v.49, no.9, pp.2034 - 2046, 2011-09 |
Reply by the Authors to the Comment by H. Liang and M. Zhu Zhao, Liang; Choi, K. K.; Lee, Ikjin, AIAA JOURNAL, v.51, no.12, pp.2990 - 2990, 2013-12 |
Sampling-based RBDO using the stochastic sensitivity analysis and Dynamic Kriging method Lee, Ikjin; Choi, K. K.; Zhao, Liang, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.44, no.3, pp.299 - 317, 2011-09 |
Sampling-Based Stochastic Sensitivity Analysis Using Score Functions for RBDO Problems With Correlated Random Variables Lee, Ikjin; Choi, K. K.; Noh, Yoojeong; Zhao, Liang; Gorsich, David, JOURNAL OF MECHANICAL DESIGN, v.133, no.2, 2011-02 |
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