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Supervised Learning Methods for Modeling Concrete Compressive Strength Prediction at High Temperature
Supervised learning algorithms are a recent trend for the prediction of mechanical properties of concrete. This paper presents AdaBoost, random forest (RF), and decision tree (DT) models for predicting the compressive strength of concrete at high temperature, based on the experimental data of 207 te...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8071252/ https://www.ncbi.nlm.nih.gov/pubmed/33920988 http://dx.doi.org/10.3390/ma14081983 |