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.
Flood Forecasting Using Machine Learning Methods
| Flood Forecasting Using Machine Learning Methods |
| Autore | Chang Fi-John |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (376 p.) |
| Soggetto non controllato |
natural hazards &
artificial neural network flood routing the Three Gorges Dam backtracking search optimization algorithm (BSA) lag analysis artificial intelligence classification and regression trees (CART) decision tree real-time optimization ensemble empirical mode decomposition (EEMD) improved bat algorithm convolutional neural networks ANFIS method of tracking energy differences (MTED) adaptive neuro-fuzzy inference system (ANFIS) recurrent nonlinear autoregressive with exogenous inputs (RNARX) disasters flood prediction ANN-based models flood inundation map ensemble machine learning flood forecast sensitivity hydrologic models phase space reconstruction water level forecast data forward prediction early flood warning systems bees algorithm random forest uncertainty soft computing data science hydrometeorology LSTM rating curve method forecasting superpixel particle swarm optimization high-resolution remote-sensing images machine learning support vector machine Lower Yellow River extreme event management runoff series empirical wavelet transform Muskingum model hydrograph predictions bat algorithm data scarce basins Wilson flood self-organizing map big data extreme learning machine (ELM) hydroinformatics nonlinear Muskingum model invasive weed optimization rainfall–runoff flood forecasting artificial neural networks flash-flood streamflow predictions precipitation-runoff the upper Yangtze River survey parameters Haraz watershed ANN time series prediction postprocessing flood susceptibility modeling rainfall-runoff deep learning database LSTM network ensemble technique hybrid neural network self-organizing map (SOM) data assimilation particle filter algorithm monthly streamflow forecasting Dongting Lake machine learning methods micro-model stopping criteria Google Maps cultural algorithm wolf pack algorithm flood events urban water bodies Karahan flood St. Venant equations hybrid & hydrologic model |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346688303321 |
Chang Fi-John
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Processing on Image and Optical Information
| Intelligent Processing on Image and Optical Information |
| Autore | Yeom Seokwon |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (324 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
change detection
NSCT variogram function structure similarity Dongting Lake ego-motion estimation hand-eye calibration IMU lidar odometry sensor fusion texture classification Gabor filter parameter optimization feature selection hybrid ant lion optimizer wireless multimedia sensor networks wildlife monitoring image extraction Hermite adaptive mean-shift biomedical imaging bone fracture calcaneus CT image segmentation zebrafish egg microscopy image processing convolutional neural network digital image correlation high-temperature measurement heat waves thermal disturbance background-oriented schlieren fermentation monitoring quality inspection process automation deep learning superellipsoid model fitting optical sensor multi-sensor face registration inner-distance Student's-t Mixtures Model image fusion continuous casting slabs surface defect classification discrete non-separable shearlet transform gray-level co-occurrence matrix kernel spectral regression block compressed sensing error resilience reconstruction image completion tensor decomposition models image interpolation image up-scaling numerical optimization ADAM machine learning stochastic gradient methods healthy and infected lemons Hyperspectral image Penicillium digitatum pathogen lemon skin dominant spectral wavelength spectral intensity ratio zebrafish larva microscopy image analysis deep neural network clustering evaluation clustering algorithm cluster validity index boundary point interior point radiographic image image processing feature extraction classifier defect detection generative models GAN (Generative adversarial networks) facial image generation database augmentation synthesis autofocus night vision goggles sparse and low-rank matrix decomposition |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557104903321 |
|
Yeom Seokwon
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||