[HTML][HTML] Integrated and intelligent remote operation centres (I2ROCs): Assessing the human–machine requirements for 21st century mining operations
M Shimaponda-Nawa, GT Nwaila - Minerals Engineering, 2024 - Elsevier
The futuristic view of smart mines is the attainment of automated self-governed mines
without human intervention throughout the value chain. However, reality entails a hybrid …
without human intervention throughout the value chain. However, reality entails a hybrid …
[HTML][HTML] Spatial prediction of groundwater withdrawal potential using shallow, hybrid, and deep learning algorithms in the Toudgha Oasis, Southeast Morocco
Water availability is a key factor in territorial sustainable development. Moreover,
groundwater constitutes the survival element of human life and ecosystems in arid oasis …
groundwater constitutes the survival element of human life and ecosystems in arid oasis …
An ensemble-based machine learning solution for imbalanced multiclass dataset during lithology log generation
The lithology log, an integral component of the master log, graphically portrays the
encountered lithological sequence during drilling operations. In addition to offering real-time …
encountered lithological sequence during drilling operations. In addition to offering real-time …
Machine learning-based delineation of geodomain boundaries: A proof-of-concept study using data from the Witwatersrand Goldfields
SE Zhang, GT Nwaila, JE Bourdeau… - Natural Resources …, 2023 - Springer
Abstract Machine-aided geological interpretation provides an opportunity for rapid and data-
driven decision-making. In disciplines such as geostatistics, the integration of machine …
driven decision-making. In disciplines such as geostatistics, the integration of machine …
[HTML][HTML] A systematic framework for compilation of critical raw material lists and their importance for South Africa
GT Nwaila, JE Bourdeau, SE Zhang, N Chipangamate… - Resources Policy, 2024 - Elsevier
Mineral resources are important contributors to the global economy and societal wellbeing.
Directly, they provide employment, revenue and taxes through the extraction, processing …
Directly, they provide employment, revenue and taxes through the extraction, processing …
Machine learning-based classification of petrofacies in fine laminated limestones
Abstract Characterization and development of hydrocarbon reservoirs depends on the
classification of lithological patterns from well log data. In thin reservoir units, limited vertical …
classification of lithological patterns from well log data. In thin reservoir units, limited vertical …
Spatial Clustering of Primary Geochemical Halos Using Unsupervised Machine Learning in Sari Gunay Gold Deposit, Iran
MH Aghahadi, G Jozanikohan, O Asghari… - Mining, Metallurgy & …, 2024 - Springer
Identifying geochemical halos is critical in locating ore deposits and detecting deeper
anomalies. This study presents an approach that combines unsupervised random forests …
anomalies. This study presents an approach that combines unsupervised random forests …