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Browse "ME-Journal Papers(저널논문)" by Author Jung, Yongsu

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Showing results 1 to 17 of 17

1	A bayesian model calibration under insufficient data environment Choo, Jeonghwan; Jung, Yongsu; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.65, no.3, 2022-03
2	A reanalysis-based multi-fidelity (RBMF) surrogate framework for efficient structural optimization Lee, Mingyu; Jung, Yongsu; Choi, Jaehoon; Lee, Ikjin, COMPUTERS & STRUCTURES, v.273, 2022-12
3	An effective active learning strategy for reliability-based design optimization under multiple simulation models Yang, Seonghyeok; Lee, Mingyu; Jung, Yongsu; Cho, Hyunkyoo; Hu, Weifei; Lee, Ikjin, STRUCTURAL SAFETY, v.107, 2024-03
4	An expected uncertainty reduction of reliability: adaptive sampling convergence criterion for Kriging-based reliability analysis Kim, Minjik; Jung, Yongsu; Lee, Mingyu; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.65, no.7, 2022-07
5	Confidence-Based Design Optimization for a More Conservative Optimum under Surrogate Model Uncertainty Caused by Gaussian Process Jung, Yongsu; Kang, Kyeonghwan; Cho, Hyunkyoo; Lee, Ikjin, JOURNAL OF MECHANICAL DESIGN, v.143, no.9, 2021-09
6	Deep Generative Design: Integration of Topology Optimization and Generative Models Oh, Sangeun; Jung, Yongsu; Kim, Seongsin; Lee, Ikjin; Kang, Namwoo, JOURNAL OF MECHANICAL DESIGN, v.141, no.11, 2019-11
7	Determination of sample size for input variables in RBDO through bi-objective confidence-based design optimization under input model uncertainty Jung, Yongsu; Cho, Hyunkyoo; Duan, Zunyi; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.61, no.1, pp.253 - 266, 2020-01
8	Distribution estimation of Johnson-Cook parameters considering correlation in quasi-static state Choo, Jeonghwan; Jung, Yongsu; Jo, Hwisang; Kim, Juhaing; Lee, Ikjin, INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, v.244, 2023-04
9	Intelligent initial point selection for MPP search in reliability-based design optimization Jung, Yongsu; Cho, Hyunkyoo; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.62, no.4, pp.1809 - 1820, 2020-10
10	Modeling, analysis, and optimization under uncertainties: a review Acar, Erdem; Bayrak, Gamze; Jung, Yongsu; Lee, Ikjin; Ramu, Palaniappan; Ravichandran, Suja Shree, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.64, no.11, pp.2909 - 2945, 2021-11
11	Modified augmented Lagrangian coordination and alternating direction method of multipliers with parallelization in non-hierarchical analytical target cascading Jung, Yongsu; Kang, Namwoo; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.58, no.2, pp.555 - 573, 2018-08
12	MPP-based approximated DRM (ADRM) using simplified bivariate approximation with linear regression Jung, Yongsu; Cho, Hyunkyoo; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.59, no.5, pp.1761 - 1773, 2019-05
13	Optimal design of experiments for optimization-based model calibration using Fisher information matrix Jung, Yongsu; Lee, Ikjin, RELIABILITY ENGINEERING & SYSTEM SAFETY, v.216, pp.107968, 2021-12
14	Optimization-based model calibration of marginal and joint output distributions utilizing analytical gradients Jo, Hwisang; Lee, Kyungeun; Lee, Mingyu; Jung, Yongsu; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.63, no.6, pp.2853 - 2868, 2021-06
15	Probabilistic analytical target cascading using kernel density estimation for accurate uncertainty propagation Jung, Yongsu; Lee, Jongmin; Lee, Mingyu; Kang, Namwoo; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.61, no.5, pp.2077 - 2095, 2020-05
16	Reliability measure approach for confidence-based design optimization under insufficient input data Jung, Yongsu; Cho, Hyunkyoo; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION , v.60, no.5, pp.1967 - 1982, 2019-11
17	Statistical model calibration and design optimization under aleatory and epistemic uncertainty Jung, Yongsu; Jo, Hwisang; Choo, Jeonghwan; Lee, Ikjin, RELIABILITY ENGINEERING & SYSTEM SAFETY, v.222, 2022-06

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