Flood Forecasting Using Machine Learning Methods

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Flood Forecasting Using Machine Learning Methods

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This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water

Detalles Bibliográficos
Otros Autores:	Chang, Fi-John (auth), Hsu, Kuolin, Chang, Li-Chiu
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	MDPI - Multidisciplinary Digital Publishing Institute 2019
Materias:	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
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009438402106719

Descripción
Sumario:	This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water
Descripción Física:	1 electronic resource (376 p.)