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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 online resource (272 p.)
Soggetto topico Research and information: general
Soggetto non controllato artificial intelligence
artificial neural networks
cascade hydropower reservoirs
cascade reservoirs
changing environments
climate change impacts
coupled models
dammed lake
data synthesis
data-scarce deglaciating river basin
degree of balance and approach
elastic-ball modification
elasticity coefficient
empirical mode decomposition
feasible search space
flood control
flood risk
flood-risk map
forecast evaluation
generalized likelihood uncertainty estimation
Generalized Likelihood Uncertainty Estimation (GLUE)
GloFAS-Seasonal
GR4J model
gravitational search algorithm
grey entropy method
highly urbanized area
Hushan reservoir
hydrodynamic modelling
hydrologic forecasting
impoundment operation
Internet of Things (IoT)
interval number
landslide
loss-benefit ratio of ecology and power generation
machine learning
machine learning model
Mahalanobis-Taguchi System
multi-objective optimal operation model
multi-objective optimization
multi-objective reservoir operation
NDVI
opposition learning
parameter uncertainty
Pareto-front optimal solution set
partial mutation
probabilistic forecast
random forest
recurrent nonlinear autoregressive with exogenous inputs (RNARX)
regional flood inundation depth
risk
Sequential Gaussian Simulation
signal-to-noise ratio
small and medium-scale rivers
Snowmelt Runoff Model
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
temporal transferability
Three Gorges Reservoir
time-varying parameter
TOPSIS
uncertainty
uncertainty analysis
Unscented Kalman Filter
urban hydrological model
urban stormwater
water resources management
western China
whole region perspective
Yangtze River
Yarlung Zangbo River
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557110703321
Chang Fi-John  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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 online resource (376 p.)
Soggetto topico History of engineering and technology
Soggetto non controllato 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
database
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
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
the Three Gorges Dam
the upper Yangtze River
time series prediction
uncertainty
urban water bodies
water level forecast
Wilson flood
wolf pack algorithm
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