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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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Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management
| Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management |
| Autore | Kisi Ozgur |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (238 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
additive regression
artificial intelligence artificial neural network atmospheric reanalysis bagging Bayesian model averaging big data calibration CWP dagging Daymet V3 EEFlux ensemble modeling extension principle flood routing fuzzy sets and systems Google Earth Engine Govindpur groundwater groundwater level prediction hydroinformatics hydrologic model improved extreme learning machine (IELM) irrigation performance Kernel extreme learning machines M5 model tree machine learning multivariate adaptive regression spline Muskingum method n/a NDVI neural network nitrogen compound nitrogen prediction non-linear modeling PACF particle swarm optimization prediction intervals prediction models principal component analysis random subspace rotation forest satellite precipitation sensitivity analysis shortwave radiation flux density South Korea spatiotemporal variation streamflow forecasting streamflow simulation support vector machine sustainability sustainable development SVM-LF SVM-RF uncertainty uncertainty analysis ungauged basin WANN water conservation water resources |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557448103321 |
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Kisi Ozgur
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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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