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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
Chang Fi-John  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Microwave Imaging and Electromagnetic Inverse Scattering Problems
Microwave Imaging and Electromagnetic Inverse Scattering Problems
Autore Di Donato Loreto
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (170 p.)
Soggetto non controllato joint sparsity
magnetic resonance imaging
near-field measurements
rank minimization
compressed sensing
array diagnosis
microwave plasma diagnostics
radar-based breast imaging
image-based approach
contraction integral equation for inversion (CIE-I)
nonlinear optimization
contrast-source inversion
electromagnetic inverse scattering problems
nonlinear problem
tomography
RCS estimation
inverse problems
discontinuous Galerkin method (DGM)
microwave imaging profilometry
electrical-property tomography
breast imaging
antenna array
finite-difference methods
adjoint inversion methods
Bayesian compressive sensing (BCS)
orthogonality sampling method
inverse scattering
linear sampling method
breast cancer
contrast source inversion (CSI)
imaging
electromagnetic inverse scattering
antenna testing
stopping criteria
3D
microwave imaging
Kolmogorov-Smirnov (K-S) test
inverse obstacles problem
5G communication
inverse source problem
ISBN 3-03921-951-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910674007403321
Di Donato Loreto  
MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui