The advent of modern data collection and storage technologies has brought about a huge
increase in data volumes with both traditional and machine learning tools struggling to …

Data-driven mineral prospectivity mapping (MPM) with random forests (RF) has been
documented in various brownfield zones hosting known mineral deposits of the type being …

This study intends to showcase the application of Extreme Gradient boosting (XGboost), a
state-of-the-art ensemble-learning technique, for district-scale mineral potential mapping …

Abstract Knowledge-driven mineral prospectivity mapping (MPM) has been practiced with
diverse algorithms for combining GIS-based predictor layers (ie, exploration targeting …

The Jiaojia-type gold deposits, hosting> 80% of gold resource in the Jiaodong Peninsula,
Eastern China, are characterized by veinlet-and disseminated-style mineralization …

回顾了国内外在矿产资源定量预测研究领域的发展历程, 对近十年来国外相关方向的文献进行了
统计对比分析, 结果显示机器学习方法已经成为矿产资源定量预测研究领域的热点方向 …

The operation of large-scale ore-forming processes triggers the development of neighboring
mineral deposits of the same or related types in a metallogenic province. While these …

Abstract Mineral Prospectivity Mapping (MPM) is a multifaceted process relying heavily on
experts' judgments. Notwithstanding the importance of human interpretations and cognitive …

The spectrum–area (S–A) fractal model is a powerful tool for decomposition of complex
anomaly patterns of gridded geochemical data. Ordinary moving average interpolation …

Two common problems affect integration of exploration criteria for mineral prospectivity
mapping (MPM) in geographic information system (GIS):(a) stochastic error associated with …