Artificial Intelligence and Digital Technologies Shaping Mineral Industry 4.0
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 443
Special Issue Editors
Interests: application of simulation techniques, including statistical and geostatistical methods, neural networks, and fuzzy and expert systems, in diverse sectors of the mineral industry; quality control for the mineral industry; mine planning and design; health and safety in mining
Interests: surface mining planning and optimization; mining economics; environmental impact assessment of mining; mining waste management; applications of digital technologies in decision making
Special Issues, Collections and Topics in MDPI journals
Interests: underground space development; underground mine design; risk assessment in underground projects; ventilation; project cost estimation and feasibility assessment; applications of artificial neural networks in geoengineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in artificial intelligence (AI) technologies have provided a new approach in solving many problems related to the mineral industry, a traditional economic activity that was heavily based on experiential knowledge. The implementation of AI, machine learning, expert and autonomous systems, intelligent process automation, advanced analytics modeling, and simulation provide many economic benefits for the mineral industry through cost reductions, energy efficiency, improved productivity and safety, and reduced environmental footprints. Particularly, the success of AI technologies is mainly due to their similarity to human perception and reasoning. The mineral industry has been particularly receptive to these methods, since many of the mining operations and processes are understood and controlled in empirical ways.
This Special Issue aims to present the current state and progress of AI technologies in the mineral industry, their range of applications, current research projects, industrial implementations, future trends, and potential applications to emerging problems in the mineral industry. The objective is to demonstrate the importance of such technologies in raw material exploration, extraction, and processing, to provide researchers and practitioners in the field with the means to present their work, and raise awareness in the academic, research, and industry community on the maturity and potential of AI technologies as the basis for developing solutions essential for the transition of traditional mining to mineral industry 4.0.
Prof. Dr. Michael Galetakis
Dr. Maria Menegaki
Dr. Andreas Benardos
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning (shallow and deep learning)
- artificial neural networks
- fuzzy inference systems
- evolutionary algorithms
- expert and autonomous systems
- digital technologies and applications
- intelligent process automation
- data science, big data, and data mining
- advanced analytics, modeling, and simulation
