Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA
| Auteur(s): |
O. Arasteh-Khoshbin
(Institute of Structural Mechanics and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany)
S. M. Seyedpour (Institute of Structural Mechanics and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany) L. Mandl (Institute of Structural Mechanics and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany) L. Lambers (Institute of Structural Mechanics and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany) T. Ricken (Institute of Structural Mechanics and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany) |
|---|---|
| Médium: | article de revue |
| Langue(s): | anglais |
| Publié dans: | European Journal of Environmental and Civil Engineering |
| Page(s): | 1-20 |
| DOI: | 10.1080/19648189.2024.2393881 |
- Informations
sur cette fiche - Reference-ID
10802509 - Publié(e) le:
10.11.2024 - Modifié(e) le:
10.11.2024
Structurae coopère avec
