Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Advances in Computational Intelligence Applications in the Mining Industry
| Advances in Computational Intelligence Applications in the Mining Industry |
| Autore | Ganguli Rajive |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (324 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
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 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557613103321 |
Ganguli Rajive
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Novel Methods and Applications for Mineral Exploration
| Novel Methods and Applications for Mineral Exploration |
| Autore | Alexandre Paul |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (264 p.) |
| Soggetto non controllato |
mineral prospectivity mapping
deep mineral exploration geochemical exploration GA-SVR cross-gradients constraints laser-induced breakdown spectroscopy lithium mineral texture bat algorithm tungsten spatial analysis data-space stream sediments exploration MT geochemical fingerprinting 3D mineral prospectivity modeling Axi deposit LIBS dual-frequency IP one-class support vector machine Kagenfels pegmatite (co)-simulation LCT gravity gradiometry Natzwiller elastic-net regularization mineral resource classification mineral exploration Vosges micro-imaging exploration targeting project pursuit multivariate transform targeting joint inversion epithermal gold deposits inversion grain size analysis niobium Variscan orogeny QEMSCAN® receiver operating characteristic model-space JORC code Jinchuan Cu–Ni sulfide deposit limestone deposit area under the curve CSAMT magnetotelluric Youden index gravity granite |
| ISBN | 3-03928-944-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404081303321 |
|
Alexandre Paul
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||