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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 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 |
| 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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Forest Fire Risk Prediction
| Forest Fire Risk Prediction |
| Autore | Nolan Rachael |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (235 p.) |
| Soggetto topico |
Biology, life sciences
Forestry & related industries Research & information: general |
| Soggetto non controllato |
acid rain
aerosol alien pathogen allochthonous species biomass burning canopy bulk density China climate change critical LFMC threshold crown fire Cupressus sempervirens direct estimation disease drought drying tests epicormic resprouter eucalyptus fire behavior fire danger fire danger rating fire management fire modeling fire regime fire risk fire season fire severity fire size fire weather fire weather patterns flammability flammability feedbacks foliar moisture content forest fire forest fire driving factors forest fire management forest fire occurrence forest/grassland fire fuel moisture fuel moisture content fuels FWI system humidity diffusion coefficients introduced fungus leaf water potential machine learning mass loss calorimeter meteorological factor regression MNI modeling moisture content n/a occurrence of forest fire plant traits PM2.5 Portugal prediction accuracy prescribed burning radiative transfer model random forest RCP remote sensing Seiridium cardinale senescence southwest China SSR temperate forest time lag variable importance vulnerability to wildfires wildfire |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557387103321 |
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Nolan Rachael
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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UAVs for Vegetation Monitoring
| UAVs for Vegetation Monitoring |
| Autore | de Castro Megías Ana |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (452 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
Acacia
agro-environmental measures artificial intelligence artificial neural network banana broad-sense heritability canopy cover canopy height century-old biochar chlorophyll content CIELab classification close remote sensing CNN container-grown contextual spatial domain/resolution convolution neural network cotton root rot crop canopy crop disease crop mapping crop monitoring curve fitting data aggregation deep learning detection performance disease detection disease diagnosis disease monitoring drone drought tolerance eddy covariance (EC) evapotranspiration (ET) Faster RCNN flight altitude forage grass forest Fusarium wilt Glycine max GRAPEX growth model high throughput field phenotyping HSV hyperspectral image analysis image segmentation Inception v2 individual plant segmentation Indonesia inference time land cover least squares support vector machine machine learning maize tassel method comparison MobileNet v2 multiple linear regression multiscale textures multispectral multispectral image multispectral imagery multispectral remote sensing NDVI neural network nitrogen stress nutrient deficiency oil palm olive groves operating parameters ornamental patch-based CNN phenotyping gap plant detection plant nitrogen estimation plant segmentation plant trails plant-by-plant plant-level precision agriculture purple rapeseed leaves random forest red-edge spectra remote sensing remote sensing technique RGB RGB camera RGB imagery semantic segmentation single-plant solar zenith angle southern Spain spatial resolution SSD sUAS support vector machine tassel branch number texture thermal thermal camera time of day transfer learning transpiration tropics Two Source Energy Balance model (TSEB) U-Net UAS UAV UAV digital images UAV hyperspectral UAV remote sensing unmanned aerial vehicle variable importance vegetation cover vegetation ground cover vegetation index vegetation indices VGG16 visual recognition water stress weed detection wheat yellow rust winter wheat biomass |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557661103321 |
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de Castro Megías Ana
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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