| Computer vision and deep learning–based data anomaly detection method for structural health monitoring Y Bao, Z Tang, H Li, Y Zhang Structural Health Monitoring 18 (2), 401-421, 2019 | 609 | 2019 |
| The state of the art of data science and engineering in structural health monitoring Y Bao, Z Chen, S Wei, Y Xu, Z Tang, H Li Engineering 5 (2), 234-242, 2019 | 438 | 2019 |
| Convolutional neural network‐based data anomaly detection method using multiple information for structural health monitoring Z Tang, Z Chen, Y Bao, H Li Structural Control and Health Monitoring 26 (1), e2296, 2019 | 392 | 2019 |
| Compressive-sensing data reconstruction for structural health monitoring: a machine-learning approach Y Bao, Z Tang, H Li Structural Health Monitoring 19 (1), 293-304, 2020 | 96 | 2020 |
| Group sparsity-aware convolutional neural network for continuous missing data recovery of structural health monitoring Z Tang, Y Bao, H Li Structural Health Monitoring 20 (4), 1738-1759, 2021 | 66 | 2021 |
| Machine‐learning‐based methods for output‐only structural modal identification D Liu, Z Tang, Y Bao, H Li Structural Control and Health Monitoring 28 (12), e2843, 2021 | 65 | 2021 |
| Deep reinforcement learning-based sampling method for structural reliability assessment Z Xiang, Y Bao, Z Tang, H Li Reliability Engineering & System Safety 199, 106901, 2020 | 59 | 2020 |
| Data anomaly detection for structural health monitoring by multi-view representation based on local binary patterns Y Zhang, Z Tang, R Yang Measurement 202, 111804, 2022 | 39 | 2022 |
| A data-driven multi-scale constitutive model of concrete material based on polynomial chaos expansion and stochastic damage model J He, R Gao, Z Tang Construction and Building Materials 334, 127441, 2022 | 23 | 2022 |
| Clarifying and quantifying the geometric correlation for probability distributions of inter-sensor monitoring data: A functional data analytic methodology Z Chen, Y Bao, Z Tang, J Chen, H Li Mechanical Systems and Signal Processing 138, 106540, 2020 | 15 | 2020 |
| Automated seismic event detection considering faulty data interference using deep learning and Bayesian fusion Z Tang, J Guo, Y Wang, W Xu, Y Bao, J He, Y Zhang Computer‐Aided Civil and Infrastructure Engineering, 2024 | 4 | 2024 |
| An interpretable deep learning method for identifying extreme events under faulty data interference J Guo, Z Tang, C Zhang, W Xu, Y Wu Applied Sciences 13 (9), 5659, 2023 | 4 | 2023 |
| Collision Study on New Aluminum Alloy W-Beam Guardrail L Wang, X Huang, R Li, Z Tang, J Li, D Chen Applied Sciences 14 (12), 5266, 2024 | 2 | 2024 |
| Three-Dimensional Reconstruction and Deformation Identification of Slope Models Based on Structured Light Method Z Chen, C Zhang, Z Tang, K Fang, W Xu Sensors 24 (3), 794, 2024 | 2 | 2024 |
| Nonuniform data loss reconstruction based on time-series-specialized neural networks for structural health monitoring P Liu, Z Tang, C Zhang, X Huang, W Xu Structural Health Monitoring, 14759217251321760, 2025 | | 2025 |
Yuequan BaoSchool of Civil Engineering, Harbin Institute of TechnologyE-mailová adresa ověřena na: hit.edu.cn
