| 近三年期刊论文
(1) Liu, Z., Tan, S., Jia, D., Sun, C., Jiang, Z., Guo, T., & Sun, Z.* (2025). Exploring scour mechanisms of bridge group under tidal Conditions: In-situ survey, laboratory experiment, and numerical analysis. Ocean Engineering, 338, 122025. (2) Zhang, Z., Fu, Y., & Sun, Z.* (2025). Advancements in digital twin-enhanced health monitoring and condition assessment of cable-supported bridges. Structures, Vol. 79, 109448. (3) Lei, X., Sun, Z.*, Wang, A., Guo, T., & Nagayama, T. (2025). Estimation of bridge girder cumulative displacement for component operational warning using Bayesian neural networks. Structural Control and Health Monitoring, 2025(1), 9974584. (4) Sun, Z., Xie, T., Li, M., & Guo, T. (2025). Quasi-real-time prediction and warning of stay cable vibration subjected to typhoon with a Nonlinear Autoregressive Neural Network and KNN. Engineering Structures, 340, 120661. (5) Lei, X., Sun, M., Sun, Z.*, Siringoringo, D. M., & Dong, Y. (2025). Data-based feature representation of traffic flow for predicting bridge displacement responses with ensemble learning model. Journal of Civil Structural Health Monitoring, 15(4), 1081-1099. (6) Ding, Z., Liu, H., Demartino, C., Feng, M., & Sun, Z.* (2024). Neighborhood component analysis-based feature selection in machine learning to predict tendon ultimate stress of unbonded prestressed concrete beams. Case Studies in Construction Materials, 21, e03428. (7) Sun, Z., Ye, X. W., & Lu, J. (2024). Estimating stay cable vibration under typhoon with an explainable ensemble learning model. Structure and Infrastructure Engineering, 20(12), 1912-1924. (8) Sun, Z., Siringoringo, D. M., Chen, S. Z., & Lu, J. (2023). Cumulative displacement-based detection of damper malfunction in bridges using data-driven isolation forest algorithm. Engineering Failure Analysis, 143, 106849. (9) Zhong, Q. M., Chen, S. Z.*, Sun, Z.*, & Tian, L. C. (2023). Fully automatic operational modal analysis method based on statistical rule enhanced adaptive clustering method. Engineering Structures, 274, 115216. (10) Sun, Z., Santos, J., Caetano, E., & Oliveira, C. (2023). Interpreting cumulative displacement in a suspension bridge with a physics-based characterisation of environment and roadway/railway loads. Journal of Civil Structural Health Monitoring, 13(2), 387-397. (11) Ye, X. W., Sun, Z.*, & Lu, J. (2023). Prediction and early warning of wind-induced girder and tower vibration in cable-stayed bridges with machine learning-based approach. Engineering Structures, 275, 115261. (12) Sun, H., Sun, Z.*, & Yao, Y. (2023). Hanger replacement and corrosion assessment in a suspension bridge. Structures, Vol. 58, 105501. (13) Sun, Z., Caetano, E., Pereira, S., & Moutinho, C. (2023). Employing histogram of oriented gradient to enhance concrete crack detection performance with classification algorithm and Bayesian optimization. Engineering Failure Analysis, 150, 107351. (14) Sun, Z., Sun, M., Siringoringo, D. M., Dong, Y., & Lei, X. (2023). Predicting bridge longitudinal displacement from monitored operational loads with hierarchical CNN for condition assessment. Mechanical Systems and Signal Processing, 200, 110623. (15) Lei, X., Siringoringo, D. M., Dong, Y., & Sun, Z.* (2023). Interpretable machine learning methods for clarification of load-displacement effects on cable-stayed bridge. Measurement, 220, 113390. (16) Feng, D. C., Wang, W. J., Mangalathu, S., & Sun, Z.* (2023). Condition Assessment of Highway Bridges Using Textual Data and Natural Language Processing‐(NLP‐) Based Machine Learning Models. Structural Control and Health Monitoring, 2023(1), 9761154.
(17) Lei, X., Siringoringo, D. M., Sun, Z.*, & Fujino, Y. (2023). Displacement response estimation of a cable-stayed bridge subjected to various loading conditions with one-dimensional residual convolutional autoencoder method. Structural Health Monitoring, 22(3), 1790-1806.
(18) Sun, Z., & Ye, X. W. (2022). Incorporating site-specific weigh-in-motion data into fatigue life assessment of expansion joints under dynamic vehicle load. Engineering Structures, 255, 113941. (19) Sun, Z., Santos, J., & Caetano, E. (2022). Vision and support vector machine–based train classification using weigh-in-motion data. Journal of Bridge Engineering, 27(6), 06022001. (20) Sun, Z., Santos, J., & Caetano, E. (2022). Data‐driven prediction and interpretation of fatigue damage in a road‐rail suspension bridge considering multiple loads. Structural Control and Health Monitoring, 29(9), e2997. (21) Sun, Z., Feng, D. C., Mangalathu, S., Wang, W. J., & Su, D. (2022). Effectiveness assessment of TMDs in bridges under strong winds incorporating machine-learning techniques. Journal of Performance of Constructed Facilities, 36(5), 04022036. (Citation: 27)
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