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Advances in Hydrologic Forecasts and Water Resources Management
| Advances in Hydrologic Forecasts and Water Resources Management |
| Autore | Chang Fi-John |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (272 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
water resources management
landslide dammed lake flood risk time-varying parameter GR4J model changing environments temporal transferability western China cascade hydropower reservoirs multi-objective optimization TOPSIS gravitational search algorithm opposition learning partial mutation elastic-ball modification Snowmelt Runoff Model parameter uncertainty data-scarce deglaciating river basin climate change impacts generalized likelihood uncertainty estimation Yangtze River cascade reservoirs impoundment operation GloFAS-Seasonal forecast evaluation small and medium-scale rivers highly urbanized area flood control whole region perspective coupled models flood-risk map hydrodynamic modelling Sequential Gaussian Simulation urban stormwater probabilistic forecast Unscented Kalman Filter artificial neural networks Three Gorges Reservoir Mahalanobis-Taguchi System grey entropy method signal-to-noise ratio degree of balance and approach interval number multi-objective optimal operation model feasible search space Pareto-front optimal solution set loss–benefit ratio of ecology and power generation elasticity coefficient empirical mode decomposition Hushan reservoir data synthesis urban hydrological model Generalized Likelihood Uncertainty Estimation (GLUE) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) uncertainty analysis NDVI Yarlung Zangbo River machine learning model random forest Internet of Things (IoT) regional flood inundation depth recurrent nonlinear autoregressive with exogenous inputs (RNARX) artificial intelligence machine learning multi-objective reservoir operation hydrologic forecasting uncertainty risk |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557110703321 |
Chang Fi-John
|
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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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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 |
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Chang Fi-John
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||