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Machine learning applications in minerals processing: A review
JT McCoy, L Auret - Minerals Engineering, 2019 - Elsevier
Abstract Machine learning and artificial intelligence techniques have an ever-increasing
presence and impact on a wide-variety of research and commercial fields. Disappointed by …
presence and impact on a wide-variety of research and commercial fields. Disappointed by …
Soft modelling of the Hardgrove grindability index of bituminous coals: An overview
Predictions of the Hardgrove grindability index, a predictor of the crushing and pulverization
propensity of coal, have been made using both regression and neural network techniques …
propensity of coal, have been made using both regression and neural network techniques …
Improvement of grinding characteristics of Indian coal by microwave pre-treatment
The influence of microwave pretreatment on the grindability of high-ash Indian coal was
investigated. Scanning electron microscope analysis characterized the micro fractures in …
investigated. Scanning electron microscope analysis characterized the micro fractures in …
Recovery and grade accurate prediction of pilot plant flotation column concentrate: Neural network and statistical techniques
In this study, the metallurgical performance (grade and recovery) forecasting of pilot plant
flotation column using Artificial Neural Networks (ANN) and Multivariate Non-Linear …
flotation column using Artificial Neural Networks (ANN) and Multivariate Non-Linear …
Prediction and optimization studies for bioleaching of molybdenite concentrate using artificial neural networks and genetic algorithm
This paper presents the application of an artificial neural network (ANN) in order to predict
the effects of operational parameters on the dissolution of Cu, Mo and Re from molybdenite …
the effects of operational parameters on the dissolution of Cu, Mo and Re from molybdenite …
Prediction of the bottom ash formed in a coal-fired power plant using artificial neural networks
The amount of bottom ash formed in a pulverized coal-fired power plant was predicted by
artificial neural network modeling using one-year operating data of the plant and the …
artificial neural network modeling using one-year operating data of the plant and the …
Prediction of coal response to froth flotation based on coal analysis using regression and artificial neural network
In this paper, the combustible value (ie 100-Ash) and combustible recovery of coal flotation
concentrate were predicted by regression and artificial neural network based on proximate …
concentrate were predicted by regression and artificial neural network based on proximate …
[HTML][HTML] Artificial neural network approach for rheological characteristics of coal-water slurry using microwave pre-treatment
Detailed experimental investigations were carried out for microwave pre-treatment of high
ash Indian coal at high power level (900 W) in microwave oven. The microwave exposure …
ash Indian coal at high power level (900 W) in microwave oven. The microwave exposure …
SHAP-based interpretation of an XGBoost model in the prediction of grindability of coals and their blends
M Rzychoń, A Żogała, L Rog - International Journal of Coal …, 2022 - Taylor & Francis
ABSTRACT The Hardgrove Grindability Index (HGI) is a measure of coal's resistance to
crushing. HGI is influenced by many factors due to the complex structure of coal. This study …
crushing. HGI is influenced by many factors due to the complex structure of coal. This study …
Hardgrove grindability index prediction using support vector regression
BV Rao, SJ Gopalakrishna - International Journal of Mineral Processing, 2009 - Elsevier
Hardgrove grindability index (HGI) measures the grindability of coal and is a qualitative
measure of coal. It is referred to in mining, beneficiation and utilization of coal. HGI of coal …
measure of coal. It is referred to in mining, beneficiation and utilization of coal. HGI of coal …