| A nested extreme response surface approach for time-dependent reliability-based design optimization Z Wang, P Wang Journal of Mechanical Design 134 (12), 121007, 2012 | 303 | 2012 |
| A maximum confidence enhancement based sequential sampling scheme for simulation-based design Z Wang, P Wang Journal of Mechanical Design 136 (2), 021006, 2014 | 175 | 2014 |
| Time-variant reliability assessment through equivalent stochastic process transformation Z Wang, W Chen Reliability Engineering & System Safety 152, 166-175, 2016 | 155 | 2016 |
| A new approach for reliability analysis with time-variant performance characteristics Z Wang, P Wang Reliability Engineering & System Safety 115, 70-81, 2013 | 148 | 2013 |
| Deep learning for high-dimensional reliability analysis M Li, Z Wang Mechanical Systems and Signal Processing, 106399, 2019 | 136 | 2019 |
| Surrogate Model Uncertainty Quantification for Reliability-based Design Optimization M Li, Z Wang Reliability Engineering & System Safety, 2019 | 131 | 2019 |
| A double-loop adaptive sampling approach for sensitivity-free dynamic reliability analysis Z Wang, P Wang Reliability Engineering & System Safety 142, 346-356, 2015 | 124 | 2015 |
| Confidence-based adaptive extreme response surface for time-variant reliability analysis under random excitation Z Wang, W Chen Structural Safety 64, 76-86, 2017 | 111 | 2017 |
| Prognostics of Lithium-Ion Batteries Using Knowledge-Constrained Machine Learning and Kalman Filtering G Bai, Y Su, MM Rahman, Z Wang Reliability Engineering & System Safety, 108944, 2022 | 68 | 2022 |
| Knowledge-informed deep networks for robust fault diagnosis of rolling bearings Y Su, L Shi, K Zhou, G Bai, Z Wang Reliability Engineering & System Safety, 109863, 2023 | 60 | 2023 |
| An Integrated Performance Measure Approach for System Reliability Analysis Z Wang, P Wang Journal of Mechanical Design 137 (2), 021406, 2015 | 50 | 2015 |
| LSTM-augmented deep networks for time-variant reliability assessment of dynamic systems M Li, Z Wang Reliability Engineering & System Safety 217, 108014, 2022 | 47 | 2022 |
| Unmanned aerial vehicle-based computer vision for structural vibration measurement and condition assessment: A concise survey K Zhou, Z Wang, YQ Ni, Y Zhang, J Tang Journal of Infrastructure Intelligence and Resilience 2 (2), 100031, 2023 | 36 | 2023 |
| Damage identification using piezoelectric electromechanical Impedance: A brief review from a numerical framework perspective P Cao, S Zhang, Z Wang, K Zhou Structures 50, 1906-1921, 2023 | 35 | 2023 |
| Confidence-driven Design Optimization Using Gaussian Process Metamodeling with Insufficient Data M Li, Z Wang Journal of Mechanical Design, 2018 | 34 | 2018 |
| Accelerated failure identification sampling for probability analysis of rare events Z Wang, P Wang Structural and Multidisciplinary Optimization 54 (1), 137-149, 2016 | 34 | 2016 |
| Recent advances in uncertainty quantification in structural response characterization and system identification K Zhou, Z Wang, Q Gao, S Yuan, J Tang Probabilistic Engineering Mechanics, 103507, 2023 | 33 | 2023 |
| Time-variant reliability-based design optimization using sequential kriging modeling M Li, G Bai, Z Wang Structural and Multidisciplinary Optimization, 1-15, 2018 | 33 | 2018 |
| Deep reliability learning with latent adaptation for design optimization under uncertainty M Li, Z Wang Computer Methods in Applied Mechanics and Engineering 397, 115130, 2022 | 26 | 2022 |
| An LSTM-based ensemble learning approach for time-dependent reliability analysis M Li, Z Wang Journal of Mechanical Design 143 (3), 2021 | 24 | 2021 |
Pingfeng WangUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
