Advances in Computational Intelligence Applications in the Mining Industry

• Autore: Ganguli Rajive
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (324 p.)
• Soggetto topico: History of engineering & technology; Technology: general issues
• Soggetto non controllato: accidents; artificial intelligence; ball mill throughput; Bayesian network; Bayesian Network Structure Learning (BNSL); bitumen extraction; bitumen processability; blast impact; bluetooth beacon; classification and regression tree; coal; convolutional neural networks; damage risk analysis; data analytics in mining; decision trees; digital twin; dimensionality reduction; discrete event simulation; empirical model; epithermal gold; fragmentation; fragmentation size analysis; gaussian naïve bayes; geological uncertainty; geostatistics; grinding circuits; health and safety management; hyperspectral imaging; image analysis; k-nearest neighbors; knowledge discovery; macerals; machine learning; masonry buildings; measurement while drilling; mine optimization; mine safety and health; mine worker fatigue; mine-to-mill; mineral prospectivity mapping; minerals processing; mining; mining equipment uncertainties; mining exploitation; mining geology; modes of operation; multispectral imaging; multivariate statistics; n/a; Naive Bayes; narratives; natural language processing; neighbourhood component analysis; non-additivity; oil sands; operational data; ore control; orebody uncertainty; partial least squares regression; petrographic analysis; point cloud scaling; Q-learning; random forest; random forest algorithm; random forest classification; random forest model; rock type; semantic segmentation; stockpiles; structure from motion; support vector machine; tactical geometallurgy; transport route; transport time; truck dispatching; underground mine; unstructured data; variable importance
• Persona (resp. second.): DessureaultSean; RogersPratt; GanguliRajive
• Sommario/riassunto: This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners.
• Titolo autorizzato: Advances in Computational Intelligence Applications in the Mining Industry
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557613103321
• Lo trovi qui: Univ. Federico II