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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 online resource (376 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
adaptive neuro-fuzzy inference system (ANFIS)
ANFIS ANN ANN-based models artificial intelligence artificial neural network artificial neural networks backtracking search optimization algorithm (BSA) bat algorithm bees algorithm big data classification and regression trees (CART) convolutional neural networks cultural algorithm data assimilation data forward prediction data scarce basins data science database decision tree deep learning disasters Dongting Lake early flood warning systems empirical wavelet transform ensemble empirical mode decomposition (EEMD) ensemble machine learning ensemble technique extreme event management extreme learning machine (ELM) flash-flood flood events flood forecast flood forecasting flood inundation map flood prediction flood routing flood susceptibility modeling forecasting Google Maps Haraz watershed high-resolution remote-sensing images hybrid & hybrid neural network hydrograph predictions hydroinformatics hydrologic model hydrologic models hydrometeorology improved bat algorithm invasive weed optimization Karahan flood lag analysis Lower Yellow River LSTM LSTM network machine learning machine learning methods method of tracking energy differences (MTED) micro-model monthly streamflow forecasting Muskingum model natural hazards & nonlinear Muskingum model optimization parameters particle filter algorithm particle swarm optimization phase space reconstruction postprocessing precipitation-runoff rainfall-runoff random forest rating curve method real-time recurrent nonlinear autoregressive with exogenous inputs (RNARX) runoff series self-organizing map self-organizing map (SOM) sensitivity soft computing St. Venant equations stopping criteria streamflow predictions superpixel support vector machine survey the Three Gorges Dam the upper Yangtze River time series prediction uncertainty urban water bodies water level forecast Wilson flood wolf pack algorithm |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346688303321 |
Chang Fi-John
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information Theory and Its Application in Machine Condition Monitoring
| Information Theory and Its Application in Machine Condition Monitoring |
| Autore | Li Yongbo |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (194 p.) |
| Soggetto topico |
History of engineering and technology
Technology: general issues |
| Soggetto non controllato |
adaptive particle swarm optimization (APSO)
anomaly detection bearing combined fault diagnosis cubic spline interpolation envelope D-S evidence theory deep learning domain adaptation empirical wavelet transform fault detection fault diagnosis gearbox grey wolf optimizer Huffman-multi-scale entropy (HMSE) improved artificial bee colony algorithm information fusion JS divergence kernel density estimation low pass FIR filter LSSVM machine vision misalignment MobileNetV3 multi-source heterogeneous fusion n/a optimal bandwidth partial transfer peak extraction rail surface defect detection rotating machinery satellite momentum wheel signal interception subdomain support vector machine support vector machine (SVM) transfer learning wind turbines YOLOv4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566460803321 |
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Li Yongbo
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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