Optimization of Mining–Mineral Processing Integration Using Unsupervised Machine Learning Algorithms

Traditional ore-waste discrimination schemes often do not take into consideration the impact of fluctuations of the head grade, which have on the performance of mineral processing facilities. This research introduces the use of target grades for processing destinations as an alternative to cut off g...

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Vydané v:	Natural resources research (New York, N.Y.) Ročník 29; číslo 5; s. 3035 - 3046
Hlavní autori:	Li, Siyi, Sari, Yuksel Asli, Kumral, Mustafa
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.10.2020 Springer Nature B.V
Predmet:	Algorithms Chemistry and Earth Sciences Cluster analysis Clustering Computer Science Cut off grades Divergence Earth and Environmental Science Earth Sciences Fossil Fuels (incl. Carbon Capture) Geography Learning algorithms Machine learning Mathematical Modeling and Industrial Mathematics Mineral processing Mineral Resources Original Paper Physics Reclassification Statistics for Engineering Sustainable Development Unsupervised learning Vector quantization Robust clustering Taguchi loss function Spectral clustering Target grades CLARA Mining and mineral processing
ISSN:	1520-7439, 1573-8981
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