Predicting Hard Rock Pillar Stability Using GBDT, XGBoost, and LightGBM Algorithms

Predicting pillar stability is a vital task in hard rock mines as pillar instability can cause large-scale collapse hazards. However, it is challenging because the pillar stability is affected by many factors. With the accumulation of pillar stability cases, machine learning (ML) has shown great pot...

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Principais autores:	Weizhang Liang, Suizhi Luo, Guoyan Zhao, Hao Wu
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2020-05-01
Serija:	Mathematics
Teme:	pillar stability hard rock prediction gradient boosting decision tree (GBDT) extreme gradient boosting (XGBoost) light gradient boosting machine (LightGBM)
Online dostop:	https://www.mdpi.com/2227-7390/8/5/765
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