0
  • DE
  • EN
  • FR
  • Base de données et galerie internationale d'ouvrages d'art et du génie civil

Publicité

Hoang D. Nguyen

La bibliographie suivante contient toutes les publications répertoriées dans la base de données qui sont reliées à ce nom en tant qu'auteur, éditeur ou collaborateur.

  1. Nguyen, Hoang D. / Kim, Chanyoung / Lee, Kihak / Shin, Myoungsu (2024): Development of data-driven models to predict seismic drift response of RC wall structures: An application of deep neural networks. Dans: Soil Dynamics and Earthquake Engineering, v. 186 (novembre 2024).

    https://doi.org/10.1016/j.soildyn.2024.108952

  2. Rhee, Jeong H. / Nguyen, Hoang D. / Kim, Moon K. / Lim, Yun M. / Kim, Gun (2024): An integrated machine-learning platform for assessing various dynamic responses of steel beams. Dans: Structures, v. 61 (mars 2024).

    https://doi.org/10.1016/j.istruc.2024.106125

  3. Nguyen, Van-Quang / Nguyen, Hoang D. / Petrone, Floriana / Park, Duhee: Rapid damage state classification for underground box tunnels using machine learning. Dans: Structure and Infrastructure Engineering.

    https://doi.org/10.1080/15732479.2023.2266709

  4. Nguyen, Hoang D. / Shin, Myoungsu / LaFave, James M. (2023): Optimal intensity measures for probabilistic seismic demand models of steel moment frames. Dans: Journal of Building Engineering, v. 65 (avril 2023).

    https://doi.org/10.1016/j.jobe.2022.105629

  5. Nguyen, Hoang D. / Dao, Nhan D. / Shin, Myoungsu (2022): Machine learning-based prediction for maximum displacement of seismic isolation systems. Dans: Journal of Building Engineering, v. 51 (juillet 2022).

    https://doi.org/10.1016/j.jobe.2022.104251

  6. Nguyen, Nam V. / Nguyen, Hoang D. / Dao, Nhan D. (2022): Machine learning models for predicting maximum displacement of triple pendulum isolation systems. Dans: Structures, v. 36 (février 2022).

    https://doi.org/10.1016/j.istruc.2021.12.024

  7. Nguyen, Hoang D. / LaFave, James M. / Lee, Young-Joo / Shin, Myoungsu (2022): Rapid seismic damage-state assessment of steel moment frames using machine learning. Dans: Engineering Structures, v. 252 (février 2022).

    https://doi.org/10.1016/j.engstruct.2021.113737

  8. Nguyen, Hoang D. / Dao, Nhan D. / Shin, Myoungsu (2021): Prediction of seismic drift responses of planar steel moment frames using artificial neural network and extreme gradient boosting. Dans: Engineering Structures, v. 242 (septembre 2021).

    https://doi.org/10.1016/j.engstruct.2021.112518

  9. Nguyen, Hoang D. / Shin, Myoungsu (2021): Effects of soil–structure interaction on seismic performance of a low-rise R/C moment frame considering material uncertainties. Dans: Journal of Building Engineering, v. 44 (décembre 2021).

    https://doi.org/10.1016/j.jobe.2021.102713

  10. Nguyen, Hoang D. / Truong, Gia Toai / Shin, Myoungsu (2021): Development of extreme gradient boosting model for prediction of punching shear resistance of r/c interior slabs. Dans: Engineering Structures, v. 235 (mai 2021).

    https://doi.org/10.1016/j.engstruct.2021.112067

  11. Nguyen, Hoang D. / Shin, Myoungsu / Torbol, Marco (2020): Reliability assessment of a planar steel frame subjected to earthquakes in case of an implicit limit-state function. Dans: Journal of Building Engineering, v. 32 (novembre 2020).

    https://doi.org/10.1016/j.jobe.2020.101782

Rechercher une publication...

Disponible seulement avec
Mon Structurae

Texte intégral
Structurae coopère avec
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine