Coupled extreme gradient boosting algorithm with artificial intelligence models for predicting compressive strength of fiber reinforced polymer- confined concrete

Accurately predicting and identifying appropriate parameters are necessary for producing a safe and reliable strength model of concrete elements confined with fiber-reinforced polymers (FRP). In this study, an extreme gradient boosting (XGBoost) algorithm was developed for the feature selection and...

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Vydané v:	Engineering applications of artificial intelligence Ročník 134; s. 108674
Hlavní autori:	Tao, Hai, Ali, Zainab Hasan, Mukhtar, Faisal, Al Zand, Ahmed W., Marhoon, Haydar Abdulameer, Goliatt, Leonardo, Yaseen, Zaher Mundher
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.08.2024
Predmet:	Artificial intelligence Composite system Confined concrete Extreme gradient boosting Fiber reinforced polymer Composite system Extreme gradient boosting Fiber reinforced polymer Artificial intelligence Confined concrete
ISSN:	0952-1976, 1873-6769
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