Supervised Learning Methods for Modeling Concrete Compressive Strength Prediction at High Temperature

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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Bibliographic Details
Main Authors: Mahmood Ahmad, Ji-Lei Hu, Feezan Ahmad, Xiao-Wei Tang, Maaz Amjad, Muhammad Junaid Iqbal, Muhammad Asim, Asim Farooq
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Materials
Subjects:
compressive strength
concrete
prediction
data mining
high temperature
sensitivity analysis
Online Access:https://www.mdpi.com/1996-1944/14/8/1983

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https://www.mdpi.com/1996-1944/14/8/1983

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