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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 2,   Pages 284-305 doi: 10.1007/s11709-022-0901-6

Abstract: Artificial neural network, random forest, and categorical gradient boosting (CatBoost) models were optimizedThe findings indicated that CatBoost outperformed the other two models with excellent predictive abilities

Keywords： compressive strength     self-compacting concrete     artificial neural network     decision tree     CatBoost    

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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

Journal Article