Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization

Accurate assessment of undrained shear strength (USS) for soft sensitive clays is a great concern in geotechnical engineering practice. This study applies novel data-driven extreme gradient boosting (XGBoost) and random forest (RF) ensemble learning methods for capturing the relationships between th...

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Veröffentlicht in:	Di xue qian yuan. 2021-01, Vol.12 (1), p.469-477
Hauptverfasser:	Zhang, Wengang, Wu, Chongzhi, Zhong, Haiyi, Li, Yongqin, Wang, Lin
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian optimization Extreme gradient boosting k-fold CV Random forest Undrained shear strength
Online-Zugang:	Volltext
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