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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Vydané v:	Advances in engineering software (1992) Ročník 173; s. 103267
Hlavní autori:	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
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.11.2022
Predmet:	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
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