A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)

A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)

Supervised machine learning and its algorithm is an emerging trend for the prediction of mechanical properties of concrete. This study uses an ensemble random forest (RF) and gene expression programming (GEP) algorithm for the compressive strength prediction of high strength concrete. The parameters...

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Bibliographic Details
Main Authors: Furqan Farooq, Muhammad Nasir Amin, Kaffayatullah Khan, Muhammad Rehan Sadiq, Muhammad Faisal Javed, Fahid Aslam, Rayed Alyousef
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Applied Sciences
Subjects:
strength concrete
prediction
genetic engineering programming
Online Access:https://www.mdpi.com/2076-3417/10/20/7330

Internet

https://www.mdpi.com/2076-3417/10/20/7330

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