Manuscript Topics

This Special Issue will focus on recent developments in the application of machine learning, artificial intelligence, and advanced numerical modelling techniques for addressing challenges in mining geomechanics, rock mass characterization, slope stability, blasting, and underground excavation design. It will also highlight the integration of experimental studies, field monitoring, and predictive modelling to improve safety, efficiency, and sustainability in mining and geotechnical engineering.

The issue will aim to bring together interdisciplinary research bridging geomechanics, data science, and mining engineering, encouraging contributions from both academia and industry. Particular emphasis will be placed on innovative methodologies, real-world case studies, and the practical implementation of intelligent systems in mining operations. Contributions addressing uncertainty quantification, risk assessment, and decision-support systems are also highly encouraged.

Suggested keywords:
Machine learning;
Artificial intelligence;
Rock mechanics;
Mining geomechanics;
Numerical modelling;
Slope stability;
Blasting optimization;
Underground excavation;
Rock mass characterization;
Predictive modelling;
Digital mining;
Smart mining systems.

Instruction for Authors
http://www.aimspress.com/aimsgeo/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/