Hai-Van Thi Mai
- (2024): 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, v. 18, n. 6 (Juni 2024).
- (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).
- (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).
- (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).
- (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).
- (2021): Development of deep neural network model to predict the compressive strength of rubber concrete. In: Construction and Building Materials, v. 301 (September 2021).
- (2021): Prediction Compressive Strength of Concrete Containing GGBFS using Random Forest Model. In: Advances in Civil Engineering, v. 2021 (Januar 2021).
Structurae kooperiert mit
