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
| Author(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) |
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | European Journal of Environmental and Civil Engineering |
| Page(s): | 1-20 |
| DOI: | 10.1080/19648189.2024.2393881 |
- About this
data sheet - Reference-ID
10802509 - Published on:
10/11/2024 - Last updated on:
10/11/2024
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