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...

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Detalles Bibliográficos
Autores principales: Ahmad, Mahmood, Hu, Ji-Lei, Ahmad, Feezan, Tang, Xiao-Wei, Amjad, Maaz, Iqbal, Muhammad Junaid, Asim, Muhammad, Farooq, Asim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8071252/
https://www.ncbi.nlm.nih.gov/pubmed/33920988
http://dx.doi.org/10.3390/ma14081983

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