研究论文
Geology-informed intelligent prediction of aquifer groutability for water-inrush control in mining with an interpretable hybrid deep learning framework
Wenxin Li, Dan Ma, Xuefeng Gao, Quanhui Liu, Chuanjiu Zhang, Baoli Wang
China University of Mining and Technology Shaanxi Yanchang Petroleum (China) China Coal Technology and Engineering Group Corp (China) CCTEG Xi'an Research Institute (China)
来源International Journal of Minerals Metallurgy and Materials
年份2026
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学术脉络
学科主题
工程Geoscience and Mining Technology
Grouting, Rheology, and Soil Mechanics · Hydrological Forecasting Using AI
参考文献 50
Static Testing of Pile-Base Post-Grouting Piles of the Suramadu Bridge
被引 62Guoliang Dai, Weiming Gong, Xueliang Zhao · Geotechnical Testing Journal · 2010
SMOTE-RSB *: a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory
被引 488Enislay Ramentol, Yailé Caballero Mota, Rafael Bello · Knowledge and Information Systems · 2011
Estimating cement take and grout efficiency on foundation improvement for Li-Yu-Tan dam
被引 32Chau-Ping Yang · Engineering Geology · 2004
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引用本文 1
Editorial for special issue on intelligent green mining
被引 0Aixiang Wu, Pathegama Gamage Ranjith, Raimund Bürger · International Journal of Minerals Metallurgy and Materials · 2026
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