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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
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Industry 4.0 for SMEs - Smart Manufacturing and Logistics for SMEs
| Industry 4.0 for SMEs - Smart Manufacturing and Logistics for SMEs |
| Autore | Rauch Erwin |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (348 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
latent semantic analysis
virtual quality management concept investigation concept disambiguation knowledge discovery sustainable methodologies small and medium sized enterprises material handling systems simulation ARENA®, time study overall equipment effectiveness manufacturing performance Industry 4.0 manufacturing sustainability manufacturing process model business process management hierarchical clustering similarity BPMN human factors cyber-physical systems cyber-physical production systems anthropocentric design Operator 4.0 human–machine interaction energy efficient operation manufacturing system stochastic event digital twin Max-plus Algebra MATLAB-Simulink advanced manufacturing industry 4.0 SME technology adoption model assembly supply chain sustainability complexity indicators testing criteria SMEs e-business modelling LSP Lifecycle Model Quality Function Deployment Best-Worst Method Internet of Things India awareness small and medium-sized enterprises assessment model collaborative robotics physical ergonomics human-robot collaboration human-centered design assembly small and medium sized enterprise positive complexity negative complexity infeasible configurations product platform customer’s perception assessment field study smart manufacturing cloud platform artificial intelligence machine learning deep learning smart logistics logistics 4.0 smart technologies sustainable agriculture plant factory |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557625503321 |
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Rauch Erwin
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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