Akademik Veri Yönetim Sistemi
Mining, Metallurgy and Exploration, 2026 (SCI-Expanded, Scopus)
Underground mining is becoming increasingly important as economically valuable ore deposits near the surface are depleting and depth of ore seam is increasing. In underground mining, miners have to deal with rock, soil and drainage systems and have to keep the production system stable, safe and secure. Due to these reasons, underground mining has difficult conditions that need to be handled scientifically and carefully. As artificial intelligence techniques are developing, mining industry has also started to benefit from the use and advantages of these methods. In this study, application of artificial intelligence techniques in underground mining methods are examined and state of the art review is presented. Application areas are classified into four headings. These are namely, rock mechanics and engineering, multi-criteria decision making, underground operations safety & health, economic analysis of mining operations. In addition, studies handled are classified according to methodology as simulation based and machine learning/deep learning based methods. All subgroups are analyzed and areas of study which need more attention in terms of artificial intelligence techniques are revealed.