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Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Phung, Ba-Nhan / Le, Thanh-Hai / Nguyen, Thuy-Anh / Hoang, Huong-Giang Thi / Ly, Hai-Bang (2023): Novel approaches to predict the Marshall parameters of basalt fiber asphalt concrete. In: Construction and Building Materials, v. 400 (Oktober 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.132847

  2. Nguyen, Thuy-Anh / Ly, Hai-Bang (2024): Predicting axial compression capacity of CFDST columns and design optimization using advanced machine learning techniques. In: Structures, v. 59 (Januar 2024).

    https://doi.org/10.1016/j.istruc.2023.105724

  3. 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 (Dezember 2023).

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

  4. Nguyen, May Huu / Nguyen, Thuy-Anh / Ly, Hai-Bang (2023): Ensemble XGBoost schemes for improved compressive strength prediction of UHPC. In: Structures, v. 57 (November 2023).

    https://doi.org/10.1016/j.istruc.2023.105062

  5. 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 (Februar 2023).

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

  6. 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 (März 2023).

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

  7. 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 (Februar 2023).

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

  8. Nguyen, Thuy-Anh / Ly, Hai-Bang / Tran, Van Quan (2022): Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees and optimization algorithms. In: Frontiers of Structural and Civil Engineering, v. 16, n. 10 (November 2022).

    https://doi.org/10.1007/s11709-022-0842-0

  9. Hoang, Huong-Giang Thi / Nguyen, Thuy-Anh / Nguyen, Hoang-Long / Ly, Hai-Bang (2022): Neural network approach for GO-modified asphalt properties estimation. In: Case Studies in Construction Materials, v. 17 (Dezember 2022).

    https://doi.org/10.1016/j.cscm.2022.e01617

  10. Nguyen, Thuy-Anh / Ly, Hai-Bang (2022): Ensemble Tree-Based Approach to Predict the Rotation Capacity of Wide-Flange Beams. In: Advances in Civil Engineering, v. 2022 (Januar 2022).

    https://doi.org/10.1155/2022/4195243

  11. Nguyen, Thuy-Anh / Trinh, Son Hoang / Nguyen, May Huu / Ly, Hai-Bang (2023): Novel ensemble approach to predict the ultimate axial load of CFST columns with different cross-sections. In: Structures, v. 47 (Januar 2023).

    https://doi.org/10.1016/j.istruc.2022.11.047

  12. Qi, Chongchong / Ly, Hai-Bang / Minh Le, Lu / Yang, Xingyu / Guo, Li / Thai Pham, Binh (2021): Improved strength prediction of cemented paste backfill using a novel model based on adaptive neuro fuzzy inference system and artificial bee colony. In: Construction and Building Materials, v. 284 (Mai 2021).

    https://doi.org/10.1016/j.conbuildmat.2021.122857

  13. 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

  14. 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 (Januar 2021).

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

  15. Ly, Hai-Bang / Nguyen, Thuy-Anh / Thai Pham, Binh (2021): Estimation of Soil Cohesion Using Machine Learning Method: A Random Forest Approach. In: Advances in Civil Engineering, v. 2021 (Januar 2021).

    https://doi.org/10.1155/2021/8873993

  16. Ly, Hai-Bang / Thai Pham, Binh (2020): Prediction of Shear Strength of Soil Using Direct Shear Test and Support Vector Machine Model. In: The Open Construction and Building Technology Journal, v. 14, n. 1 (18 Februar 2020).

    https://doi.org/10.2174/1874836802014010268

  17. Ly, Hai-Bang / Thai Pham, Binh (2020): Soil Unconfined Compressive Strength Prediction Using Random Forest (RF) Machine Learning Model. In: The Open Construction and Building Technology Journal, v. 14, n. 1 (18 Februar 2020).

    https://doi.org/10.2174/1874836802014010278

  18. Ly, Hai-Bang / Thai Pham, Binh (2020): Prediction of Shear Strength of Soil Using Direct Shear Test and Support Vector Machine Model. In: The Open Construction and Building Technology Journal, v. 14, n. 1 (18 Februar 2020).

    https://doi.org/10.2174/1874836802014010041

  19. Tran, Van Quan / Nguyen, Hoang Long / Dao, Van Dong / Hilloulin, Benoit / Nguyen, Long Khanh / Nguyen, Quang Hung / Le, Tien-Thinh / Ly, Hai-Bang (2021): Temperature effects on chloride binding capacity of cementitious materials. In: Magazine of Concrete Research, v. 73, n. 15 (August 2021).

    https://doi.org/10.1680/jmacr.19.00484

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