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Flood Forecasting Using Machine Learning Methods

Authors: --- ---
ISBN: 9783038975489 Year: Pages: 376 DOI: 10.3390/books978-3-03897-549-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-03-08 11:42:05
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Abstract

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

Keywords

data scarce basins --- runoff series --- data forward prediction --- ensemble empirical mode decomposition (EEMD) --- stopping criteria --- method of tracking energy differences (MTED) --- deep learning --- convolutional neural networks --- superpixel --- urban water bodies --- high-resolution remote-sensing images --- monthly streamflow forecasting --- artificial neural network --- ensemble technique --- phase space reconstruction --- empirical wavelet transform --- hybrid neural network --- flood forecasting --- self-organizing map --- bat algorithm --- particle swarm optimization --- flood routing --- Muskingum model --- machine learning methods --- St. Venant equations --- rating curve method --- nonlinear Muskingum model --- hydrograph predictions --- flood routing --- Muskingum model --- hydrologic models --- improved bat algorithm --- Wilson flood --- Karahan flood --- flood susceptibility modeling --- ANFIS --- cultural algorithm --- bees algorithm --- invasive weed optimization --- Haraz watershed --- ANN-based models --- flood inundation map --- self-organizing map (SOM) --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- ensemble technique --- artificial neural networks --- uncertainty --- streamflow predictions --- sensitivity --- flood forecasting --- extreme learning machine (ELM) --- backtracking search optimization algorithm (BSA) --- the upper Yangtze River --- deep learning --- LSTM network --- water level forecast --- the Three Gorges Dam --- Dongting Lake --- Muskingum model --- wolf pack algorithm --- parameters --- optimization --- flood routing --- flash-flood --- precipitation-runoff --- forecasting --- lag analysis --- random forest --- machine learning --- flood prediction --- flood forecasting --- hydrologic model --- rainfall–runoff, hybrid & --- ensemble machine learning --- artificial neural network --- support vector machine --- natural hazards & --- disasters --- adaptive neuro-fuzzy inference system (ANFIS) --- decision tree --- survey --- classification and regression trees (CART), data science --- big data --- artificial intelligence --- soft computing --- extreme event management --- time series prediction --- LSTM --- rainfall-runoff --- flood events --- flood forecasting --- data assimilation --- particle filter algorithm --- micro-model --- Lower Yellow River --- ANN --- hydrometeorology --- flood forecasting --- real-time --- postprocessing --- machine learning --- early flood warning systems --- hydroinformatics --- database --- flood forecast --- Google Maps

Power Electronics in Renewable Energy Systems

Authors: ---
ISBN: 9783039210442 / 9783039210459 Year: Pages: 604 DOI: 10.3390/books978-3-03921-045-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

This book offers a collection of 30 scientific papers which address the problems associated with the use of power electronic converters in renewable energy source-based systems. Relevant problems associated with the use of power electronic converters to integrate renewable energy systems to the power grid are presented. Some of the covered topics relate to the integration of photovoltaic and wind energy generators into the rest of the system, and to the use of energy storage to mitigate power fluctuations, which are a characteristic of renewable energy systems. The book provides a good overview of the abovementioned topics.

Keywords

modular multilevel converter --- battery energy storage system --- state-of-charge balancing --- second-life battery --- multi-energy complementary --- microgrid --- demand response --- operation optimization --- electricity price --- peak-current-mode control --- dynamic modeling --- duty-ratio constraints --- discontinuous conduction mode --- FACTS devices --- active power filter --- static compensator --- control strategies --- grid-connected converter --- SPWM --- SVM --- maximum power point tracking --- open circuit voltage --- perturb and observe --- thermoelectric generator --- two-stage photovoltaic power --- virtual synchronous generator --- adaptive-MPPT (maximum power point tracking) --- improved-VSG (virtual synchronous generator) --- power matching --- failure zone --- governor --- frequency regulation --- inverter --- voltage-type control --- static frequency characteristics --- grid-connected converter --- adaptive resonant controller --- PLL --- impedance analysis --- distorted grid --- digital signal processor (DSP) TMS320F28335 --- grid-connected inverter --- internal model --- linear quadratic regulator --- LCL filter --- photovoltaic systems --- multilevel power converter --- soft switching --- selective harmonic mitigation --- phase shifted --- voltage cancellation --- adaptive control --- sliding mode control --- speed control --- wind energy system --- microgrid (MG) --- droop control --- washout filter --- hardware in the loop (HIL) --- active front-end converter --- back-to-back converter --- permanent magnet synchronous generator (PMSG) --- THD --- type-4 wind turbine --- wind energy system --- Opal-RT Technologies® --- synchronization --- adaptive notch filter (ANF) --- phase-locked loop (PLL) --- wind power prediction --- phase space reconstruction --- multivariate linear regression --- cloud computing --- time series --- multiple VSGs --- oscillation mitigation --- coordinated control --- small-signal and transient stability --- coordination control --- energy storage --- grid support function --- inertia --- photovoltaic --- virtual synchronous generator --- weak grid --- parallel inverters --- oscillation suppression --- notch filter --- impedance reshaping --- boost converter --- peak-current-mode control --- dynamic modeling --- discontinuous operation mode --- doubly-fed induction generator --- short-circuit fault --- frequency regulation --- variable power tracking control --- improved additional frequency control --- variable coefficient regulation --- inertia and damping characteristics --- generator speed control --- electrical power generation --- turbine and generator --- grid-connected converter --- organic Rankine cycle --- renewable energy --- multiport converter (MPC) --- single ended primary inductor converter (SEPIC) --- multi-input single output (MISO) --- renewable power system --- coupled oscillators --- virtual impedance --- synchronization --- power converters --- droop control --- virtual admittance --- distributed generation --- energy --- renewable energy --- microgrids --- Energy Internet --- energy router --- microgrid --- electric vehicle --- PV --- battery-energy storage --- DC-AC power converters --- impedance emulation --- stability analysis --- power-hardware-in- the-loop --- photovoltaic generators --- maximum power point tracking --- step size --- perturbation frequency --- source and load impedance --- transient dynamics --- stability --- grid synchronization --- power electronics --- power grid --- inverter --- grid-connected --- microgrid --- experiment --- modules --- synchronverter --- power ripple elimination --- resonant controller --- unbalanced power grid --- ROCOF --- PLL --- error --- low inertia --- VSC --- n/a

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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CC by-nc-nd (2)


Language

eng (2)


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2019 (2)