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Sediment Transport in Coastal Waters

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ISBN: 9783038978442 9783038978459 Year: Pages: 284 DOI: 10.3390/books978-3-03897-845-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Oceanography
Added to DOAB on : 2019-04-25 16:37:17
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Abstract

The interface of 440,000 km long coastline in the world is subject to global change, with an increasing human pressure (land use, buildings, sand mining, dredging) and increasing population. Improving our knowledge on involved mechanisms and sediment transport processes, monitoring the evolution of sedimentary stocks and anticipating changes in littoral and coastal zones is essential for this purpose. The special issue of Water on “Sediment transport in coastal waters” gathers thirteen papers which introduce the current revolution in the scientific research related to coastal and littoral hydrosedimentary dynamics, and reflect the diversity of concerns on which research in coastal sediment transport is based, and current trends — topics and preferred methods — to address them.

Keywords

suspended sediment --- sediment transport --- coastal hydraulics --- Mekong --- river plume --- monsoon --- mathematical model --- geochemical map --- particle transfer process --- tidal current --- analysis of variance (ANOVA) --- Cluster analysis --- Mahalanobis’ generalized distances --- Seto Inland Sea --- East Coast Low --- nearshore processes --- coastal erosion --- coastal management --- climate change --- numerical modelling --- Southeast Australia --- soil erosion --- SWAT --- water scarcity --- sediment transport modelling --- Tafna catchment --- North Africa --- suspended sediment --- sediment transport --- lagoon --- geochemistry --- Ni mining --- sediment trap --- hydrodynamics --- New Caledonia --- dry season --- Senegal River delta --- Langue de Barbarie spit --- delta vulnerability --- river-mouth migration --- spit breaching --- ERA hindcast waves --- longshore sediment transport --- Vietnam --- South China Sea --- erosion --- recovery --- storminess --- winter monsoon --- typhoons --- shoreline --- waves forcing --- storms --- resilience --- post-storm recovery --- Bight of Benin --- seasonal cycle --- trend --- sand-mud mixture erosion --- numerical modelling --- non-cohesive to cohesive transition --- remote sensing reflectance --- turbidity --- seagrass beds --- bed shear stress --- fresh water runoff --- oceanic water intrusion --- suspended particulate matter --- aggregates --- flocculation --- biomass --- sediment --- turbidity --- remote-sensing --- MODerate Resolution Imaging Spectroradiometer (MODIS) --- Support Vector Regression (SVR) --- oligotrophic lagoon --- bathymetry --- reflectance --- seabed colour --- coral reef --- New Caledonia --- sediment transport --- cohesive sediments --- non cohesive sediments --- sand --- mud --- coastal erosion --- sedimentation --- morphodynamics --- suspended particulate matter --- bedload

Intelligent Optimization Modelling in Energy Forecasting

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ISBN: 9783039283644 9783039283651 Year: Pages: 262 DOI: 10.3390/books978-3-03928-365-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2020-04-07 23:07:09
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Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.

Keywords

short-term load forecasting --- weighted k-nearest neighbor (W-K-NN) algorithm --- comparative analysis --- empirical mode decomposition (EMD) --- particle swarm optimization (PSO) algorithm --- intrinsic mode function (IMF) --- support vector regression (SVR) --- short term load forecasting --- crude oil price forecasting --- time series forecasting --- hybrid model --- complementary ensemble empirical mode decomposition (CEEMD) --- sparse Bayesian learning (SBL) --- multi-step wind speed prediction --- Ensemble Empirical Mode Decomposition --- Long Short Term Memory --- General Regression Neural Network --- Brain Storm Optimization --- substation project cost forecasting model --- feature selection --- data inconsistency rate --- modified fruit fly optimization algorithm --- deep convolutional neural network --- multi-objective grey wolf optimizer --- long short-term memory --- fuzzy time series --- LEM2 --- combination forecasting --- wind speed --- electrical power load --- crude oil prices --- time series forecasting --- improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) --- kernel learning --- kernel ridge regression --- differential evolution (DE) --- artificial intelligence techniques --- energy forecasting --- condition-based maintenance --- asset management --- renewable energy consumption --- Gaussian processes regression --- state transition algorithm --- five-year project --- forecasting --- Markov-switching --- Markov-switching GARCH --- energy futures --- commodities --- portfolio management --- active investment --- diversification --- institutional investors --- energy price hedging --- metamodel --- ensemble --- individual --- regression --- interpolation

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english (2)


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