Hoang D. Nguyen
- Development of data-driven models to predict seismic drift response of RC wall structures: An application of deep neural networks. In: Soil Dynamics and Earthquake Engineering, v. 186 (November 2024). (2024):
- An integrated machine-learning platform for assessing various dynamic responses of steel beams. In: Structures, v. 61 (März 2024). (2024):
- Rapid damage state classification for underground box tunnels using machine learning. In: Structure and Infrastructure Engineering. :
- Optimal intensity measures for probabilistic seismic demand models of steel moment frames. In: Journal of Building Engineering, v. 65 (April 2023). (2023):
- Machine learning-based prediction for maximum displacement of seismic isolation systems. In: Journal of Building Engineering, v. 51 (Juli 2022). (2022):
- Machine learning models for predicting maximum displacement of triple pendulum isolation systems. In: Structures, v. 36 (Februar 2022). (2022):
- Rapid seismic damage-state assessment of steel moment frames using machine learning. In: Engineering Structures, v. 252 (Februar 2022). (2022):
- Prediction of seismic drift responses of planar steel moment frames using artificial neural network and extreme gradient boosting. In: Engineering Structures, v. 242 (September 2021). (2021):
- Effects of soil–structure interaction on seismic performance of a low-rise R/C moment frame considering material uncertainties. In: Journal of Building Engineering, v. 44 (Dezember 2021). (2021):
- Development of extreme gradient boosting model for prediction of punching shear resistance of r/c interior slabs. In: Engineering Structures, v. 235 (Mai 2021). (2021):
- Reliability assessment of a planar steel frame subjected to earthquakes in case of an implicit limit-state function. In: Journal of Building Engineering, v. 32 (November 2020). (2020):