Machine Learning—A Review of Applications in Mineral Resource Estimation

Mineral resource estimation involves the determination of grade and tonnage a mineral deposit based on its geological characteristics using various methods. Conventional methods, such as geometric geostatistical techniques, remain most widely used methods for estimation. However, recent advances in computer algorithms have allowed researchers to explore potential machine learning techniques This study presents comprehensive review papers that employed estimate resources. The covers popular their implementation limitations. Papers performed comparative analysis both conventional were also considered. literature shows models can accommodate several parameters effectively approximate complex nonlinear relationships among them, exhibiting superior performance over techniques.