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Browse by Subject Surrogate model

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Showing results 1 to 16 of 16

1	A nonlinearity integrated bi-fidelity surrogate model based on nonlinear mapping Li, Kunpeng; Li, Qingye; Lv, Liye; Song, Xueguan; Ma, Yunsheng; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.66, no.9, 2023-09
2	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
3	An efficient differential evolution using speeded-up k-nearest neighbor estimator Park, So Youn; Lee, Ju-Jang, SOFT COMPUTING, v.18, no.1, pp.35 - 49, 2014-01
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	Equivalent target probability of failure to convert high-reliability model to low-reliability model for efficiency of sampling-based RBDO Lee, Ikjin; Shin, Jaekwan; Choi, K. K., STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.48, no.2, pp.235 - 248, 2013-08
6	Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design Zhou, Teng; Gani, Rafiqul; Sundmacher, Kai, ENGINEERING, v.7, no.9, pp.1231 - 1238, 2021-09
7	Modified screening-based Kriging method with cross validation and application to engineering design Kang, Kyeonghwan; Qin, Caiyan; Lee, Bong Jae; Lee, Ikjin, APPLIED MATHEMATICAL MODELLING, v.70, pp.626 - 642, 2019-06
8	Numerical investigation for erratic behavior of Kriging surrogate model Kwon, Hyung Il; Yi, Seulgi; Choi, Seongim, JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, v.28, no.9, pp.3697 - 3707, 2014-09
9	Robust design optimization (RDO) of thermoelectric generator system using non-dominated sorting genetic algorithm II (NSGA-II) Lee, Ungki; Park, Sudong; Lee, Ikjin, ENERGY, v.196, 2020-04
10	Sampling-based approach for design optimization in the presence of interval variables Yoo, David; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.49, no.2, pp.253 - 266, 2014-02
11	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
12	Sequential surrogate modeling for efficient finite element model updating Jin, Seung-Seop; Jung, Hyung-Jo, COMPUTERS & STRUCTURES, v.168, pp.30 - 45, 2016-05
13	Small failure probability: principles, progress and perspectives Lee, Ikjin; Lee, Ungki; Ramu, Palaniappan; Yadav, Deepanshu; Bayrak, Gamze; Acar, Erdem, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.65, no.11, 2022-11
14	Surrogate model for optimizing annealing duration of self-assembled membrane-cavity structures Jeong, Mun Goung; Kim, Taeyeong; Lee, Bong Jae; Lee, Jungchul, MICRO AND NANO SYSTEMS LETTERS, v.10, no.1, 2022-06
15	Variable selection using Gaussian process regression-based metrics for high-dimensional model approximation with limited data Lee, Kyungeun; Cho, Hyunkyoo; Lee, Ikjin, STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, v.59, no.5, pp.1439 - 1454, 2019-05
16	대리모델을 이용한 현가장치의 부싱 강성 곡선 최적화에 관한 연구 = A Study on the Optimization of Bushing Stiffness in Suspension System using Surrogate Model link 김수호; 윤성기; et al, 한국과학기술원, 2017

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