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Hai-Van Thi Mai

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. Hoang, Huong-Giang Thi / Mai, Hai-Van Thi / Nguyen, Hoang Long / Ly, Hai-Bang: Application of extreme gradient boosting in predicting the viscoelastic characteristics of graphene oxide modified asphalt at medium and high temperatures. In: Frontiers of Structural and Civil Engineering.

    https://doi.org/10.1007/s11709-024-1025-y

  2. Phung, Ba Nhan / Le, Thanh-Hai / Mai, Hai-Van Thi / Nguyen, Thuy-Anh / Ly, Hai-Bang (2023): Advancing basalt fiber asphalt concrete design: A novel approach using gradient boosting and metaheuristic algorithms. In: Case Studies in Construction Materials, v. 19 (December 2023).

    https://doi.org/10.1016/j.cscm.2023.e02528

  3. Mai, Hai-Van Thi / Nguyen, May Huu / Trinh, Son Hoang / Ly, Hai-Bang (2023): Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete. In: Frontiers of Structural and Civil Engineering, v. 17, n. 2 (February 2023).

    https://doi.org/10.1007/s11709-022-0901-6

  4. Mai, Hai-Van Thi / Nguyen, May Huu / Trinh, Son Hoang / Ly, Hai-Bang (2023): Toward improved prediction of recycled brick aggregate concrete compressive strength by designing ensemble machine learning models. In: Construction and Building Materials, v. 369 (March 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.130613

  5. Mai, Hai-Van Thi / Nguyen, May Huu / Ly, Hai-Bang (2023): Development of machine learning methods to predict the compressive strength of fiber-reinforced self-compacting concrete and sensitivity analysis. In: Construction and Building Materials, v. 367 (February 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.130339

  6. Ly, Hai-Bang / Nguyen, Thuy-Anh / Mai, Hai-Van Thi / Tran, Van Quan (2021): Development of deep neural network model to predict the compressive strength of rubber concrete. In: Construction and Building Materials, v. 301 (September 2021).

    https://doi.org/10.1016/j.conbuildmat.2021.124081

  7. Mai, Hai-Van Thi / Nguyen, Thuy-Anh / Ly, Hai-Bang / Tran, Van Quan (2021): Prediction Compressive Strength of Concrete Containing GGBFS using Random Forest Model. In: Advances in Civil Engineering, v. 2021 (January 2021).

    https://doi.org/10.1155/2021/6671448

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