Intelligent regional subsurface prediction based on limited borehole data and interpretability stacking technique of ensemble learning

This study introduces an intelligent method for regional subsurface prediction using a Stacking ensemble learning approach, which incorporates K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), Gradient Boosted Decision Trees (GBDT), and Xgboost as base classifiers, with Logistic Reg...

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Veröffentlicht in:Bulletin of engineering geology and the environment 2024-07, Vol.83 (7), p.272, Article 272
Hauptverfasser: Bai, Jun, Wang, Sheng, Xu, Qiang, Zhu, Junsheng, Li, Zhaoqi, Lai, Kun, Liu, Xingyi, Chen, Zongjie
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Sprache:eng
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