| The prediction of dam displacement time series using STL, extra-trees, and stacked LSTM neural network Y Li, T Bao, J Gong, X Shu, K Zhang Ieee Access 8, 94440-94452, 2020 | 75 | 2020 |
| A large-scale sensor missing data imputation framework for dams using deep learning and transfer learning strategy Y Li, T Bao, H Chen, K Zhang, X Shu, Z Chen, Y Hu Measurement 178, 109377, 2021 | 52 | 2021 |
| A new dam structural response estimation paradigm powered by deep learning and transfer learning techniques Y Li, T Bao, Z Gao, X Shu, K Zhang, L Xie, Z Zhang Structural Health Monitoring 21 (3), 770-787, 2022 | 46 | 2022 |
| VAE-TALSTM: a temporal attention and variational autoencoder-based long short-term memory framework for dam displacement prediction X Shu, T Bao, Y Li, J Gong, K Zhang Engineering with Computers, 1-16, 2022 | 30 | 2022 |
| A missing sensor measurement data reconstruction framework powered by multi-task Gaussian process regression for dam structural health monitoring systems Y Li, T Bao, Z Chen, Z Gao, X Shu, K Zhang Measurement 186, 110085, 2021 | 28 | 2021 |
| A hybrid model integrating principal component analysis, fuzzy C-means, and Gaussian process regression for dam deformation prediction Y Li, T Bao, X Shu, Z Chen, Z Gao, K Zhang Arabian Journal for Science and Engineering 46, 4293-4306, 2021 | 28 | 2021 |
| A deep residual neural network framework with transfer learning for concrete dams patch-level crack classification and weakly-supervised localization Y Li, T Bao, B Xu, X Shu, Y Zhou, Y Du, R Wang, K Zhang Measurement 188, 110641, 2022 | 27 | 2022 |
| A novel seepage behavior prediction and lag process identification method for concrete dams using HGWO-XGBoost model K Zhang, C Gu, Y Zhu, S Chen, B Dai, Y Li, X Shu IEEE Access 9, 23311-23325, 2021 | 23 | 2021 |
| Dam safety evaluation based on interval-valued intuitionistic fuzzy sets and evidence theory X Shu, T Bao, Y Li, K Zhang, B Wu Sensors 20 (9), 2648, 2020 | 19 | 2020 |
| Underwater crack pixel-wise identification and quantification for dams via lightweight semantic segmentation and transfer learning Y Li, T Bao, X Huang, H Chen, B Xu, X Shu, Y Zhou, Q Cao, J Tu, R Wang, ... Automation in Construction 144, 104600, 2022 | 18 | 2022 |
| BIM and ontology-based knowledge management for dam safety monitoring Y Zhou, T Bao, X Shu, Y Li, Y Li Automation in Construction 145, 104649, 2023 | 16 | 2023 |
| A robust real‐time method for identifying hydraulic tunnel structural defects using deep learning and computer vision Y Li, T Bao, T Li, R Wang Computer‐Aided Civil and Infrastructure Engineering 38 (10), 1381-1399, 2023 | 14 | 2023 |
| Data-driven crack behavior anomaly identification method for concrete dams in long-term service using offline and online change point detection Y Li, T Bao, X Shu, Z Gao, J Gong, K Zhang Journal of Civil Structural Health Monitoring 11, 1449-1460, 2021 | 14 | 2021 |
| Unsupervised dam anomaly detection with spatial–temporal variational autoencoder X Shu, T Bao, Y Zhou, R Xu, Y Li, K Zhang Structural Health Monitoring 22 (1), 39-55, 2023 | 12 | 2023 |
| A coupled model for dam foundation seepage behavior monitoring and forecasting based on variational mode decomposition and improved temporal convolutional network Y Zhu, Z Zhang, C Gu, Y Li, K Zhang, M Xie Structural Control and Health Monitoring 2023, 1-17, 2023 | 11 | 2023 |
| Dam anomaly assessment based on sequential variational autoencoder and evidence theory X Shu, T Bao, R Xu, Y Li, K Zhang Applied Mathematical Modelling 98, 576-594, 2021 | 11 | 2021 |
| A mathematical-mechanical hybrid driven approach for determining the deformation monitoring indexes of concrete dam K Zhang, C Gu, Y Zhu, Y Li, X Shu Engineering Structures 277, 115353, 2023 | 9 | 2023 |
| Dam safety assessment through data-level anomaly detection and information fusion Y Zhou, X Shu, T Bao, Y Li, K Zhang Structural Health Monitoring 22 (3), 2002-2021, 2023 | 5 | 2023 |
| Multi-expert attention network for long-term dam displacement prediction Y Zhou, T Bao, G Li, X Shu, Y Li Advanced Engineering Informatics 57, 102060, 2023 | 3 | 2023 |
| An integrated underwater structural multi-defects automatic identification and quantification framework for hydraulic tunnel via machine vision and deep learning Y Li, T Bao, X Huang, R Wang, X Shu, B Xu, J Tu, Y Zhou, K Zhang Structural Health Monitoring 22 (4), 2360-2383, 2023 | 3 | 2023 |
Zexun ChenLecturer in Predictive Analytics at University of EdinburghVerified email at ed.ac.uk
