Machine learning
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Article
From sessions to strategy: Revealing long-term and emerging innovation trends in data analytics, intelligent systems and automation
The Society for Mining, Metallurgy & Exploration (SME) MINEXCHANGE SME Annual Conference & Expo hosts innovation-related content across division sessions…
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Technical Abstracts
Hybrid machine learning with metaheuristic optimization for predicting blast-induced peak particle velocity in openpit mines
Blast-induced ground vibration remains one of the most critical environmental and safety challenges in openpit mining. Excessive vibration can damage…
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Technical Abstracts
Evaluation of AI-based regression models for predicting heat stress (WBGT) in underground mines
Heat stress conditions in underground mines have a significant impact on the health, safety and productivity of miners. Therefore, accurate…
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Technical Abstracts
Tunnel overbreak prediction: An integrated approach using 3D photogrammetry and machine learning
In civil and mining engineering applications, predicting overbreak is crucial to optimize excavation processes and ensure safety. This study presents…
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Article
A machine learning approach to lithology classification in mining using measurement while drilling and exploration data
Accurate lithology classification is essential as variations in rock formations can significantly impact the cost and efficiency of mineral exploration…
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Technical Abstracts
Predicting haul truck travel times in underground mines
The accurate prediction of haul truck (HT) travel times (TTs) in underground mines is critical for short-term operational planning. Unlike…
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Technical Abstracts
New approach on the development of operational fleet management systems using adaptative AI techniques: Analysis of adaptative goal weights
Truck-shovel dispatch systems based on linear or nonlinear programming algorithms have been in operation since the mid-1980s, with different levels…
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Technical Abstracts
Development of novel hybrid intelligent predictive models for dilution prediction in underground sublevel mining
Tenuous dilution estimates in underground mine production scheduling continue to cause significant variations between schedule forecasts and actual production. This…
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Technical Abstracts
Estimation of Fe grade at an ore deposit using extreme gradient boosting trees (XGBoost)
Estimating the spatial distribution of ore grade is one of the most critical steps to proceed with an investment decision…
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Lithium
Unlocking Arkansas’ Hidden Treasure: USGS Uses Machine Learning to Show Large Lithium Potential in the Smackover Formation
Using a combination of water testing and machine learning, a U.S. Geological Survey-led study estimated between 5 and 19 million…
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