AIMC Topic: Mining

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Web application using machine learning to predict cardiovascular disease and hypertension in mine workers.

Scientific reports
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 201...

Machine learning and regression in the management of runoff in bauxite mines under rehabilitation.

Environmental science and pollution research international
Accurate and reliable forecasting of monthly runoff considering several years of rehabilitation helps in planning and managing the water resources system of bauxite mining areas. A combination of linear regression models and artificial intelligence w...

Mining soil heavy metal inversion based on Levy Flight Cauchy Gaussian perturbation sparrow search algorithm support vector regression (LSSA-SVR).

Ecotoxicology and environmental safety
Soil heavy metal pollution in mining areas poses severe challenges to the ecological environment. In recent years, machine learning has been widely used in heavy metal inversion by hyperspectral data. However, deterministic algorithms and probabilist...

Prediction for the recycle of phosphate tailings in enhanced gravity field based on machine learning and interpretable analysis.

Waste management (New York, N.Y.)
Recleaning phosphate tailings using the low-cost enhanced gravity separation method is beneficial for maximizing the recovery of phosphorus element. A machine learning framework was constructed to predict the target variables of the yield, grade, and...

Deciphering geochemical fingerprints and health implications of groundwater fluoride contamination in mica mining regions using machine learning tactics.

Environmental geochemistry and health
The contribution of mica mining activities to fluoride (F) contamination in groundwater has been chased in this study. For the purpose, groundwater samples (n = 40, replicated thrice) were collected during the post-monsoons (September-October) from a...

Promoting safety of underground machinery operators through participatory ergonomics and fuzzy model analysis to foster sustainable mining practices.

Scientific reports
One of the most vital parameters to achieve sustainability in any field is encompassing the Occupational Health and Safety (OHS) of the workers. In mining industry where heavy earth moving machineries are largely employed, ergonomic hazards turn out ...

Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.

Environmental geochemistry and health
Mining activities have resulted in a substantial accumulation of cadmium (Cd) in agricultural soils, particularly in southern China. Long-term Cd exposure can cause plant growth inhibition and various diseases. Rapid identification of the extent of s...

Radiological characterization of the tailings of an abandoned copper mine using a neural network and geostatistical analysis through the Co-Kriging method.

Environmental geochemistry and health
The radiological characterization of soil contaminated with natural radionuclides enables the classification of the area under investigation, the optimization of laboratory measurements, and informed decision-making on potential site remediation. Neu...

Evaluation of mine ecological environment based on fuzzy hierarchical analysis and grey relational degree.

Environmental research
In order to improve the level of mine ecological environment management and restoration, and to improve and enhance the overall environmental quality of mines. This study takes coal mine as the perspective, and constructs evaluation indexes in two st...