3D Mineral Prospectivity Mapping of Zaozigou Gold Deposit, West Qinling, China: Deep Learning-Based Mineral Prediction

نویسندگان

چکیده

This paper focuses on the scientific problem of quantitative mineralization prediction at large depth in Zaozigou gold deposit, west Qinling, China. Five geological and geochemical indicators are used to establish model. Machine learning Deep algorithms employed for 3D Mineral Prospectivity Mapping (MPM). Especially, Student Teacher Ore-induced Anomaly Detection (STOAD) model is proposed based knowledge distillation (KD) idea combined with Auto-encoder (DAE) network Compared DAE, STOAD uses three outputs anomaly detection can make full use information from multiple levels data greater overall robustness. The results show that mineral resources by applying has a good performance, where value Area Under Curve (AUC) 0.97. Finally, main exploration targets delineated further investigation.

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ژورنال

عنوان ژورنال: Minerals

سال: 2022

ISSN: ['2075-163X']

DOI: https://doi.org/10.3390/min12111382