Flood Forecasting Using Machine Learning Methods

• Autore: Chang Fi-John
• Pubblicazione: 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
• Persona (resp. second.): HsuKuolin; ChangLi-Chiu
• Sommario/riassunto: This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water
• Titolo autorizzato: Flood Forecasting Using Machine Learning Methods
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910346688303321
• Lo trovi qui: Univ. Federico II