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Título de Acceso Abierto

Advances in Computational Intelligence Applications in the Mining Industry

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

truck dispatching; mining equipment uncertainties; orebody uncertainty; discrete event simulation; Q-learning; grinding circuits; minerals processing; random forest; decision trees; machine learning; knowledge discovery; variable importance; mineral prospectivity mapping; random forest algorithm; epithermal gold; unstructured data; blast impact; empirical model; mining; fragmentation; mine worker fatigue; random forest model; health and safety management; stockpiles; operational data; mine-to-mill; geostatistics; ore control; mine optimization; digital twin; modes of operation; geological uncertainty; multivariate statistics; partial least squares regression; oil sands; bitumen extraction; bitumen processability; mine safety and health; accidents; narratives; natural language processing; random forest classification; hyperspectral imaging; multispectral imaging; dimensionality reduction; neighbourhood component analysis; artificial intelligence; mining exploitation; masonry buildings; damage risk analysis; Bayesian network; Naive Bayes; Bayesian Network Structure Learning (BNSL); rock type; mining geology; bluetooth beacon; classification and regression tree; gaussian naïve bayes; k-nearest neighbors; support vector machine; transport route; transport time; underground mine; tactical geometallurgy; data analytics in mining; ball mill throughput; measurement while drilling; non-additivity; coal; petrographic analysis; macerals; image analysis; semantic segmentation; convolutional neural networks; point cloud scaling; fragmentation size analysis; structure from motion; n/a

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-0365-3158-8

País de edición

Suiza