| An active learning kriging model for hybrid reliability analysis with both random and interval variables X Yang, Y Liu, Y Gao, Y Zhang, Z Gao Structural and Multidisciplinary Optimization 51, 1003-1016, 2015 | 197 | 2015 |
| System reliability analysis through active learning Kriging model with truncated candidate region X Yang, Y Liu, C Mi, C Tang Reliability Engineering & System Safety 169, 235-241, 2018 | 118 | 2018 |
| Probability and convex set hybrid reliability analysis based on active learning Kriging model X Yang, Y Liu, Y Zhang, Z Yue Applied Mathematical Modelling 39 (14), 3954-3971, 2015 | 104 | 2015 |
| A system reliability analysis method combining active learning Kriging model with adaptive size of candidate points X Yang, C Mi, D Deng, Y Liu Structural and Multidisciplinary Optimization 60, 137-150, 2019 | 65 | 2019 |
| Hybrid reliability analysis with both random and probability-box variables X Yang, Y Liu, Y Zhang, Z Yue Acta Mechanica 226, 1341-1357, 2015 | 65 | 2015 |
| Active learning Kriging model combining with kernel-density-estimation-based importance sampling method for the estimation of low failure probability X Yang, Y Liu, C Mi, X Wang Journal of Mechanical Design 140 (5), 051402, 2018 | 59 | 2018 |
| Unified reliability analysis by active learning Kriging model combining with random‐set based Monte Carlo simulation method X Yang, Y Liu, Y Gao International Journal for Numerical Methods in Engineering 108 (11), 1343-1361, 2016 | 52 | 2016 |
| Structural reliability analysis under evidence theory using the active learning kriging model X Yang, Y Liu, P Ma Engineering Optimization 49 (11), 1922-1938, 2017 | 39 | 2017 |
| System reliability analysis with small failure probability based on active learning Kriging model and multimodal adaptive importance sampling X Yang, X Cheng, T Wang, C Mi Structural and Multidisciplinary Optimization 62, 581–596, 2020 | 32 | 2020 |
| A novel active learning method for profust reliability analysis based on the Kriging model X Yang, X Cheng, Z Liu, T Wang Engineering with Computers, 1-14, 2022 | 28 | 2022 |
| Active learning method combining Kriging model and multimodal‐optimization‐based importance sampling for the estimation of small failure probability X Yang, X Cheng International Journal for Numerical Methods in Engineering 121 (21), 4843-4864, 2020 | 28 | 2020 |
| Estimation of low failure probability based on active learning Kriging model with a concentric ring approaching strategy X Yang, Y Liu, X Fang, C Mi Structural and Multidisciplinary Optimization 58 (3), 1175–1186, 2018 | 26 | 2018 |
| Bounds approximation of limit‐state surface based on active learning Kriging model with truncated candidate region for random‐interval hybrid reliability analysis X Yang, T Wang, J Li, Z Chen International Journal for Numerical Methods in Engineering 121 (7), 1345-1366, 2020 | 17 | 2020 |
| An enhanced active learning Kriging model for evidence theory-based reliability analysis X Yang, L Zeqing, X Cheng Structural and Multidisciplinary Optimization 64, 2165–2181, 2021 | 13 | 2021 |
| Matching of multiple aerodynamic parameters for railway train/tunnel systems to ensure critical airtightness performance of high-speed trains J Niu, D Lv, R Li, D Zhou, Y Wang, X Yang Structural and Multidisciplinary Optimization 66 (1), 4, 2023 | 11 | 2023 |
| An efficient hybrid reliability analysis method based on active learning Kriging model and multimodal‐optimization‐based importance sampling T Wang, X Yang, M Caiying International Journal for Numerical Methods in Engineering 122 (24), 7664- 7682, 2021 | 10 | 2021 |
| An adaptive method fusing the kriging model and multimodal importance sampling for profust reliability analysis X Yang, X Cheng, Z Liu, T Wang Engineering Optimization 54 (11), 1870-1886, 2022 | 4 | 2022 |
| 含认知不确定性参数的高效高精度可靠性分析方法研究 杨旭锋 西北工业大学, 2016 | 4 | 2016 |
| 飞机起落架收放机构功能可靠性与灵敏度分析 杨旭锋， 刘永寿， 何勇 航空制造技术 57 (3), 78-81, 2014 | 4 | 2014 |
| Error-guided method combining adaptive learning kriging model and parallel-tempering-based importance sampling for system reliability analysis T Wang, X Yang, C Mi Engineering Optimization 56 (4), 525-547, 2024 | 2 | 2024 |
