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
| Autor(en): |
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) |
|---|---|
| Medium: | Fachartikel |
| Sprache(n): | Englisch |
| Veröffentlicht in: | European Journal of Environmental and Civil Engineering |
| Seite(n): | 1-20 |
| DOI: | 10.1080/19648189.2024.2393881 |
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Datenseite - Reference-ID
10802509 - Veröffentlicht am:
10.11.2024 - Geändert am:
10.11.2024
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