Flood Forecasting Using Machine Learning Methods

Flood Forecasting Using Machine Learning Methods

E-kirja

Chang, Fi-John , auth

;

Hsu, Kuolin , auth

;

Chang, Li-Chiu , auth

MDPI - Multidisciplinary Digital Publishing Institute 2019

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1 electronic resource (376 p.)

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englanti

Alkuteoksen kieli

englanti

Julkaisija

MDPI - Multidisciplinary Digital Publishing Institute, 2019

Aiheet

natural hazards &

artificial neural network

the Three Gorges Dam

backtracking search optimization algorithm (BSA)

artificial intelligence

classification and regression trees (CART)

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)

flood prediction

ANN-based models

flood inundation map

ensemble machine learning

hydrologic models

phase space reconstruction

water level forecast

data forward prediction

early flood warning systems

hydrometeorology

LSTM

rating curve method

particle swarm optimization

high-resolution remote-sensing images

machine learning

support vector machine

Lower Yellow River

extreme event management

empirical wavelet transform

Muskingum model

hydrograph predictions

data scarce basins

self-organizing map

extreme learning machine (ELM)

hydroinformatics

nonlinear Muskingum model

invasive weed optimization

rainfall–runoff

flood forecasting

artificial neural networks

streamflow predictions

precipitation-runoff

the upper Yangtze River

survey

Haraz watershed

ANN

time series prediction

flood susceptibility modeling

rainfall-runoff

ensemble technique

hybrid neural network

self-organizing map (SOM)

data assimilation

particle filter algorithm

monthly streamflow forecasting

machine learning methods

stopping criteria

cultural algorithm

wolf pack algorithm

urban water bodies

St. Venant equations

hydrologic model

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