| Variable importance analysis: A comprehensive review P Wei, Z Lu, J Song Reliability Engineering & System Safety 142, 399-432, 2015 | 461 | 2015 |
| A new learning function for Kriging and its applications to solve reliability problems in engineering Z Lv, Z Lu, P Wang Computers & Mathematics with Applications 70 (5), 1182-1197, 2015 | 325 | 2015 |
| Subset simulation for structural reliability sensitivity analysis S Song, Z Lu, H Qiao Reliability Engineering & System Safety 94 (2), 658-665, 2009 | 288 | 2009 |
| Reliability sensitivity method by line sampling Z Lu, S Song, Z Yue, J Wang Structural Safety 30 (6), 517-532, 2008 | 216 | 2008 |
| Nataf transformation based point estimate method HS Li, ZZ Lü, XK Yuan Chinese Science Bulletin 53 (17), 2586-2592, 2008 | 209 | 2008 |
| Efficient structural reliability analysis method based on advanced Kriging model L Zhang, Z Lu, P Wang Applied Mathematical Modelling 39 (2), 781-793, 2015 | 172 | 2015 |
| Efficient sampling methods for global reliability sensitivity analysis P Wei, Z Lu, W Hao, J Feng, B Wang Computer Physics Communications 183 (8), 1728-1743, 2012 | 168 | 2012 |
| Moment-independent importance measure of basic random variable and its probability density evolution solution LJ Cui, ZZ Lü, XP Zhao Science China Technological Sciences 53, 1138-1145, 2010 | 167 | 2010 |
| Support vector machine for structural reliability analysis H Li, Z Lü, Z Yue Applied Mathematics and Mechanics 27 (10), 1295-1303, 2006 | 141 | 2006 |
| AK-SYSi: an improved adaptive Kriging model for system reliability analysis with multiple failure modes by a refined U learning function W Yun, Z Lu, Y Zhou, X Jiang Structural and Multidisciplinary Optimization 59, 263-278, 2019 | 127 | 2019 |
| 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 |
| An application of the Kriging method in global sensitivity analysis with parameter uncertainty P Wang, Z Lu, Z Tang Applied Mathematical Modelling 37 (9), 6543-6555, 2013 | 108 | 2013 |
| Monte Carlo simulation for moment-independent sensitivity analysis P Wei, Z Lu, X Yuan Reliability Engineering & System Safety 110, 60-67, 2013 | 105 | 2013 |
| 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 |
| A novel learning function based on Kriging for reliability analysis Y Shi, Z Lu, R He, Y Zhou, S Chen Reliability Engineering & System Safety 198, 106857, 2020 | 94 | 2020 |
| AK-ARBIS: an improved AK-MCS based on the adaptive radial-based importance sampling for small failure probability W Yun, Z Lu, X Jiang, L Zhang, P He Structural Safety 82, 101891, 2020 | 94 | 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 |
| New validation metrics for models with multiple correlated responses W Li, W Chen, Z Jiang, Z Lu, Y Liu Reliability Engineering & System Safety 127, 1-11, 2014 | 84 | 2014 |
Pengfei WeiNorthwestern Polytechnical UniversityVerified email at nwpu.edu.cn
