Flood Forecasting Using Machine Learning Methods

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

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Bibliographische Detailangaben
Hauptverfasser:	Chang, Fi-John, Hsu, Kuolin, Chang, Li-Chiu
Format:	E-Book
Sprache:	Englisch
Veröffentlicht:	MDPI - Multidisciplinary Digital Publishing Institute 01.02.2019
Schlagworte:	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 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 History of engineering and technology 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 T1-995 TA1-2040 TA170-171 Technology, Engineering, Agriculture, Industrial processes Technology: general issues the Three Gorges Dam the upper Yangtze River time series prediction uncertainty urban water bodies water level forecast Wilson flood wolf pack algorithm
ISBN:	3038975486, 9783038975489
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water
ISBN:	3038975486 9783038975489
DOI:	10.3390/books978-3-03897-549-6