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The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Zhang, Hong / He, Jiangxia / Jiang, Xiaogang / Gong, Yanfeng / Hu, Tianyu / Jiang, Tengjiao / Zhou, Jianting: Quantitative Characterization of Surface Defects on Bridge Cable based on Improved YOLACT++. In: Case Studies in Construction Materials.

    https://doi.org/10.1016/j.cscm.2024.e03953

  2. Chen, Mingyang / Xin, Jingzhou / Tang, Qizhi / Hu, Tianyu / Zhou, Yin / Zhou, Jianting (2024): Explainable machine learning model for load-deformation correlation in long-span suspension bridges using XGBoost-SHAP. In: Developments in the Built Environment, v. 20 (December 2024).

    https://doi.org/10.1016/j.dibe.2024.100569

  3. Hu, Tianyu / Zhang, Hong / Khodadadi, Nima / Taffese, Woubishet Zewdu / Nanni, Antonio (2024): Enhancing bond strength prediction at UHPC-NC interface: A data-driven approach with augmentation and explainability. In: Construction and Building Materials, v. 451 (November 2024).

    https://doi.org/10.1016/j.conbuildmat.2024.138757

  4. Li, Houxuan / Zhang, Hong / Zhou, Jianting / Xia, Runchuan / Gong, Yanfeng / Hu, Tianyu (2024): Fatigue life prediction of corroded steel wires: An accurate and explainable data-driven approach. In: Construction and Building Materials, v. 450 (November 2024).

    https://doi.org/10.1016/j.conbuildmat.2024.138637

  5. Cheng, Cheng / Taffese, Woubishet Zewdu / Hu, Tianyu (2024): Accurate Prediction of Punching Shear Strength of Steel Fiber-Reinforced Concrete Slabs: A Machine Learning Approach with Data Augmentation and Explainability. In: Buildings, v. 14, n. 5 (24 April 2024).

    https://doi.org/10.3390/buildings14051223

  6. Li, Haolin / Yin, Xinsheng / Sha, Lirong / Yang, Dongdong / Hu, Tianyu (2023): Data-Driven Prediction Model for High-Strength Bolts in Composite Beams. In: Buildings, v. 13, n. 11 (26 October 2023).

    https://doi.org/10.3390/buildings13112769

  7. Yu, Yong / Hu, Tianyu (2023): Machine Learning Based Compressive Strength Prediction Model for CFRP-confined Columns. In: KSCE Journal of Civil Engineering, v. 28, n. 1 (1 December 2023).

    https://doi.org/10.1007/s12205-023-0827-0

  8. Hu, Tianyu / Zhang, Hong / Zhou, Jianting (2023): Machine learning-based model for recognizing the failure modes of FRP-strengthened RC beams in flexure. In: Case Studies in Construction Materials, v. 18 (July 2023).

    https://doi.org/10.1016/j.cscm.2023.e02076

  9. Li, Haolin / Yang, Dongdong / Hu, Tianyu (2023): Data-Driven Model for Predicting the Compressive Strengths of GFRP-Confined Reinforced Concrete Columns. In: Buildings, v. 13, n. 5 (27 April 2023).

    https://doi.org/10.3390/buildings13051309

  10. Hu, Tianyu / Zhang, Hong / Zhou, Jianting (2023): Prediction of the Debonding Failure of Beams Strengthened with FRP through Machine Learning Models. In: Buildings, v. 13, n. 3 (26 February 2023).

    https://doi.org/10.3390/buildings13030608

  11. Li, Guibing / Hu, Tianyu / Shao, Yian / Bai, Dawei (2022): Data-driven model for predicting intermediate crack induced debonding of FRP-strengthened RC beams in flexure. In: Structures, v. 41 (July 2022).

    https://doi.org/10.1016/j.istruc.2022.05.023

  12. Hu, Tianyu / Li, Guibing (2022): Machine Learning-Based Model in Predicting the Plate-End Debonding of FRP-Strengthened RC Beams in Flexure. In: Advances in Civil Engineering, v. 2022 (January 2022).

    https://doi.org/10.1155/2022/6069871

  13. Li, Guibing / Hu, Tianyu / Bai, Dawei (2021): BP Neural Network Improved by Sparrow Search Algorithm in Predicting Debonding Strain of FRP-Strengthened RC Beams. In: Advances in Civil Engineering, v. 2021 (January 2021).

    https://doi.org/10.1155/2021/9979028

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