| Adaptive sparse polynomial chaos expansions for global sensitivity analysis based on support vector regression K Cheng, Z Lu Computers & Structures 194, 86-96, 2018 | 127 | 2018 |
| Mixed kernel function support vector regression for global sensitivity analysis K Cheng, Z Lu, Y Wei, Y Shi, Y Zhou Mechanical Systems and Signal Processing 96, 201-214, 2017 | 110 | 2017 |
| Surrogate-assisted global sensitivity analysis: an overview K Cheng, Z Lu, C Ling, S Zhou Structural and Multidisciplinary Optimization 61, 1187-1213, 2020 | 104 | 2020 |
| Structural reliability analysis based on ensemble learning of surrogate models K Cheng, Z Lu Structural Safety 83, 101905, 2020 | 102 | 2020 |
| Global sensitivity analysis using support vector regression K Cheng, Z Lu, Y Zhou, Y Shi, Y Wei Applied Mathematical Modelling 49, 587-598, 2017 | 93 | 2017 |
| Adaptive Bayesian support vector regression model for structural reliability analysis K Cheng, Z Lu Reliability Engineering & System Safety 206, 107286, 2021 | 79 | 2021 |
| Sparse polynomial chaos expansion based on D-MORPH regression K Cheng, Z Lu Applied Mathematics and Computation 323, 17-30, 2018 | 75 | 2018 |
| Temporal and spatial multi-parameter dynamic reliability and global reliability sensitivity analysis based on the extreme value moments Y Shi, Z Lu, K Cheng, Y Zhou Structural and Multidisciplinary Optimization 56, 117-129, 2017 | 74 | 2017 |
| AK-DS: An adaptive Kriging-based directional sampling method for reliability analysis X Zhang, Z Lu, K Cheng Mechanical Systems and Signal Processing 156, 107610, 2021 | 67 | 2021 |
| A Bayesian Monte Carlo-based method for efficient computation of global sensitivity indices Y Zhou, Z Lu, K Cheng, W Yun Mechanical Systems and Signal Processing 117, 498-516, 2019 | 57 | 2019 |
| Multi-level multi-fidelity sparse polynomial chaos expansion based on Gaussian process regression K Cheng, Z Lu, Y Zhen Computer Methods in Applied Mechanics and Engineering 349, 360-377, 2019 | 41 | 2019 |
| Reliability index function approximation based on adaptive double-loop Kriging for reliability-based design optimization X Zhang, Z Lu, K Cheng Reliability Engineering & System Safety 216, 108020, 2021 | 38 | 2021 |
| Cross-entropy-based directional importance sampling with von Mises-Fisher mixture model for reliability analysis X Zhang, Z Lu, K Cheng Reliability Engineering & System Safety 220, 108306, 2022 | 36 | 2022 |
| Active learning Bayesian support vector regression model for global approximation K Cheng, Z Lu Information Sciences 544, 549-563, 2021 | 35 | 2021 |
| An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework Y Zhou, Z Lu, K Cheng, C Ling Computer Methods in Applied Mechanics and Engineering 352, 654-674, 2019 | 30 | 2019 |
| Estimation of small failure probability using generalized subset simulation K Cheng, Z Lu, S Xiao, J Lei Mechanical Systems and Signal Processing 163, 108114, 2022 | 24 | 2022 |
| Multivariate output global sensitivity analysis using multi-output support vector regression K Cheng, Z Lu, K Zhang Structural and Multidisciplinary Optimization 59, 2177-2187, 2019 | 24 | 2019 |
| Rare event estimation with sequential directional importance sampling K Cheng, I Papaioannou, Z Lu, X Zhang, Y Wang Structural Safety 100, 102291, 2023 | 23 | 2023 |
| A novel reliability sensitivity analysis method based on directional sampling and Monte Carlo simulation X Zhang, Z Lu, K Cheng, Y Wang Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2020 | 23 | 2020 |
| Time-variant reliability analysis based on high dimensional model representation K Cheng, Z Lu Reliability Engineering & System Safety 188, 310-319, 2019 | 23 | 2019 |
Yan ShiLeibniz University HannoverVerified email at mail.nwpu.edu.cn
