Prediction of strength and analysis in self-compacting concrete using machine learning based regression techniques

•The main objective of this work is to develop regression models for forecasting self-compacting concrete compressive strength that are based on machine learning.•The correctness of the model can be evaluated based on the RMSE value, as well as MSE, MAE, and R2.•The Random forest algorithm also perf...

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Bibliographic Details

Published in:	Advances in engineering software (1992) Vol. 173; p. 103267
Main Authors:	Rajakarunakaran, Surya Abisek, Lourdu, Arun Raja, Muthusamy, Suresh, Panchal, Hitesh, Jawad Alrubaie, Ali, Musa Jaber, Mustafa, Ali, Mohammed Hasan, Tlili, Iskander, Maseleno, Andino, Majdi, Ali, Ali, Shahul Hameed Masthan
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2022
Subjects:	Compression strength Decision tree Machine learning Random forest Regression Self-compacting concrete Regression Self-compacting concrete Random forest Decision tree Compression strength Machine learning
ISSN:	0965-9978
Online Access:	Get full text
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