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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Advances in engineering software (1992) Jg. 173; S. 103267
Hauptverfasser:	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
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.11.2022
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!