Numerical Model and Artificial Intelligence in Mining Engineering
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".
Deadline for manuscript submissions: 31 March 2025 | Viewed by 16
Special Issue Editor
Special Issue Information
Dear Colleagues,
We invite you to contribute to this Special Issue on “Numerical Model and Artificial Intelligence in Mining Engineering”, with original research focused on numerical simulations or artificial intelligence techniques addressing engineering challenges in the mining sector.
In this Special Issue, original research articles and reviews are welcome. Topics of interest include but are not limited to, rock mechanics, drilling and blasting, rockburst prevention, and the application of machine learning techniques in mining engineering.
With the rapid advancement of computer technology, numerical simulation and artificial intelligence have emerged as innovative tools for addressing mining-related challenges. Numerical simulation technology allows for analyzing material unit scales, enabling researchers to gain a deeper understanding of on-site engineering issues and to analyze the underlying scientific principles. Artificial intelligence, as one of today's leading-edge technologies, mimics the process of human brain learning and knowledge application, offering novel solutions to complex nonlinear problems in mining. Consequently, new theories, technologies, and practical applications in these two areas merit significant attention.
We look forward to receiving your contributions.
Dr. Zhi Yu
Guest Editor
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- surface mining
- underground mining
- rock mechanics
- drilling and blasting
- rockburst
- finite element method
- discrete element method
- machine learning technique
- deep-learning theory
- metaheuristic algorithm
