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Applications of Computational Intelligence to Power Systems

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ISBN: 9783039217601 / 9783039217618 Year: Pages: 116 DOI: 10.3390/books978-3-03921-761-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-11-08 11:31:56
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Electric power systems around the world are changing in terms of structure, operation, management and ownership due to technical, financial, and ideological reasons. Power systems keep on expanding in terms of geographical areas, asset additions, and the penetration of new technologies in generation, transmission, and distribution. The conventional methods for solving the power system design, planning, operation, and control problems have been extensively used for different applications, but these methods suffer from several difficulties, thus providing suboptimal solutions. Computationally intelligent methods can offer better solutions for several conditions and are being widely applied in electrical engineering applications. This Special Issue represents a thorough treatment of computational intelligence from an electrical power system engineer’s perspective. Thorough, well-organised, and up-to-date, it examines in detail some of the important aspects of this very exciting and rapidly emerging technology, including machine learning, particle swarm optimization, genetic algorithms, and deep learning systems. Written in a concise and flowing manner by experts in the area of electrical power systems who have experience in the application of computational intelligence for solving many complex and difficult power system problems, this Special Issue is ideal for professional engineers and postgraduate students entering this exciting field.

Entropy Measures for Data Analysis: Theory, Algorithms and Applications

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ISBN: 9783039280322 / 9783039280339 Year: Pages: 260 DOI: 10.3390/books978-3-03928-033-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2020-01-07 09:21:22
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Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Keywords

experiment of design --- empirical mode decomposition --- signal analysis --- similarity indices --- synchronization analysis --- auditory attention --- entropy measure --- linear discriminant analysis (LDA) --- support vector machine (SVM) --- auditory attention classifier --- electroencephalography (EEG) --- vague entropy --- distance induced vague entropy --- distance --- complex fuzzy set --- complex vague soft set --- entropy, entropy visualization --- entropy balance equation --- Shannon-type relations --- multivariate analysis --- machine learning evaluation --- data transformation --- sample entropy --- treadmill walking --- center of pressure displacement --- dual-tasking --- analog circuit --- fault diagnosis --- cross wavelet transform --- Tsallis entropy --- parametric t-distributed stochastic neighbor embedding --- support vector machine --- information transfer --- Chinese stock sectors --- effective transfer entropy --- market crash --- system coupling --- cross-visibility graphs --- image entropy --- geodesic distance --- Dempster-Shafer evidence theory --- uncertainty of basic probability assignment --- belief entropy --- plausibility transformation --- weighted Hartley entropy --- Shannon entropy --- learning --- information --- novelty detection --- non-probabilistic entropy --- learning systems --- permutation entropy --- embedded dimension --- short time records --- signal classification --- relevance analysis --- global optimization --- meta-heuristic --- firefly algorithm --- cross-entropy method --- co-evolution --- symbolic analysis --- ordinal patterns --- Permutation entropy --- conditional entropy of ordinal patterns --- Kolmogorov-Sinai entropy --- algorithmic complexity --- information entropy --- particle size distribution --- selfsimilar measure --- simulation --- data analysis --- entropy --- entropy measures --- automatic learning

Advances in Near Infrared Spectroscopy and Related Computational Methods

Authors: ---
ISBN: 9783039280520 / 9783039280537 Year: Pages: 496 DOI: 10.3390/books978-3-03928-053-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Chemistry (General) --- Analytical Chemistry
Added to DOAB on : 2020-01-30 16:39:46
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In the last few decades, near-infrared (NIR) spectroscopy has distinguished itself as one of the most rapidly advancing spectroscopic techniques. Mainly known as an analytical tool useful for sample characterization and content quantification, NIR spectroscopy is essential in various other fields, e.g. NIR imaging techniques in biophotonics, medical applications or used for characterization of food products. Its contribution in basic science and physical chemistry should be noted as well, e.g. in exploration of the nature of molecular vibrations or intermolecular interactions. One of the current development trends involves the miniaturization and simplification of instrumentation, creating prospects for the spread of NIR spectrometers at a consumer level in the form of smartphone attachments—a breakthrough not yet accomplished by any other analytical technique. A growing diversity in the related methods and applications has led to a dispersion of these contributions among disparate scientific communities. The aim of this Special Issue was to bring together the communities that may perceive NIR spectroscopy from different perspectives. It resulted in 30 contributions presenting the latest advances in the methodologies essential in near-infrared spectroscopy in a variety of applications.

Keywords

hyperspectral imaging --- variety discrimination --- Chrysanthemum --- deep convolutional neural network --- DNA --- FTIR spectroscopy --- rapid identification --- PLS-DA --- animal origin --- near-infrared hyperspectral imaging --- raisins --- support vector machine --- pixel-wise --- object-wise --- maize kernel --- hyperspectral imaging technology --- accelerated aging --- principal component analysis --- support vector machine model --- standard germination tests --- blackberries --- Rubus fructicosus --- phenolics --- carotenoids --- bioanalytical applications --- near infrared --- chemometrics --- VIS/NIR hyperspectral imaging --- corn seed --- classification --- freeze-damaged --- image processing --- imaging visualization --- wavelength selection --- NIR spectroscopy --- binary dragonfly algorithm --- ensemble learning --- quantitative analysis modeling --- NIR --- SCiO --- pocket-sized spectrometer --- cheese --- fat --- moisture --- multivariate data analysis --- Fourier-transform near-infrared spectroscopy --- glucose --- fructose --- dry matter --- partial least square regression --- Ewing sarcoma --- Fourier transform infrared spectroscopy --- FTIR --- chemotherapy --- bone cancer --- calibration transfer --- NIR spectroscopy --- PLS --- quantitative analysis model --- melamine --- FT-IR --- NIR spectroscopy --- quantum chemical calculation --- anharmonic calculation --- overtones --- combination bands --- near infrared spectroscopy --- Trichosanthis Fructus --- geographical origin --- chemometric techniques --- crude drugs --- prepared slices --- support vector machine-discriminant analysis --- near-infrared fluorescence --- fluorescent probes --- Zn(II) --- di-(2-picolyl)amine --- living cells --- cellular imaging --- near-infrared (NIR) spectroscopy --- calibration transfer --- affine invariance --- multivariate calibration --- partial least squares (PLS) --- NIR --- direct model transferability --- MicroNIR™ --- SVM --- hier-SVM --- SIMCA --- PLS-DA --- TreeBagger --- PLS --- calibration transfer --- agriculture --- photonics --- imaging --- spectral imaging --- spectroscopy --- handheld near-infrared spectroscopy --- pasta/sauce blends --- partial least squares calibration --- nutritional parameters --- bootstrapping soft shrinkage --- partial least squares --- extra virgin olive oil --- adulteration --- FT-NIR spectroscopy --- near-infrared spectroscopy --- ethanol --- anharmonic quantum mechanical calculations --- isotopic substitution --- overtones --- combinations bands --- seeds vitality --- rice seeds --- near-infrared spectroscopy --- hyperspectral image --- discriminant analysis --- near-infrared spectroscopy --- counter propagation artificial neural network --- detection --- auxiliary diagnosis --- BRAF V600E mutation --- colorectal cancer --- tissue --- paraffin-embedded --- deparaffinized --- stained --- ultra-high performance liquid chromatography --- Folin–Ciocalteu --- total hydroxycinnamic derivatives --- phytoextraction --- near-infrared spectroscopy --- origin traceability --- data fusion --- Paris polyphylla var. yunnanensis --- Fourier transform mid-infrared spectroscopy --- near-infrared spectroscopy --- aquaphotomics --- water --- light --- near infrared spectroscopy --- water-mirror approach --- perturbation --- biomeasurements --- biodiagnosis --- biomonitoring --- Vitis vinifera L. --- proximal sensing --- precision viticulture --- near infrared --- chemometrics --- non-destructive sensor --- NIRS --- osteopathy --- late preterm --- brain --- splanchnic --- Raman spectroscopy --- hyperspectral imaging --- analytical spectroscopy --- counterfeit and substandard pharmaceuticals --- DFT calculations --- chemometrics --- PLSR --- API --- lumefantrine --- artemether --- antimalarial tablets --- FT-NIR spectroscopy --- PLS-R --- water --- glucose --- test set validation --- RMSEP --- hyperspectral image processing --- perfusion measurements --- clinical classifications --- n/a

Groundwater Resources and Salt Water Intrusion in a Changing Environment

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ISBN: 9783039211975 / 9783039211982 Year: Pages: 176 DOI: 10.3390/books978-3-03921-198-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:16
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This Special Issue presents the work of 30 scientists from 11 countries. It confirms that the impacts of global change, resulting from both climate change and increasing anthropogenic pressure, are huge on worldwide coastal areas (and critically so on some islands in the Pacific Ocean), with highly negative effects on coastal groundwater resources, which are widely affected by seawater intrusion. Some improved research methods are proposed in the contributions: using innovative hydrogeological, geophysical, and geochemical monitoring; assessing impacts of the changing environment on the coastal groundwater resources in terms of quantity and quality; and using modelling, especially to improve management approaches. The scientific research needed to face these challenges must continue to be deployed by different approaches based on the monitoring, modelling and management of groundwater resources. Novel and more efficient methods must be developed to keep up with the accelerating pace of global change.

Statistical Analysis and Stochastic Modelling of Hydrological Extremes

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ISBN: 9783039216642 / 9783039216659 Year: Pages: 294 DOI: 10.3390/books978-3-03921-665-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Meteorology and Climatology
Added to DOAB on : 2019-12-09 16:10:12
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Hydrological extremes have become a major concern because of their devastating consequences and their increased risk as a result of climate change and the growing concentration of people and infrastructure in high-risk zones. The analysis of hydrological extremes is challenging due to their rarity and small sample size, and the interconnections between different types of extremes and becomes further complicated by the untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The complexity of analyzing hydrological extremes calls for robust statistical methods for the treatment of such events. This Special Issue is motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions. The papers of this Special Issue focus on six topics associated with hydrological extremes: Historical changes in hydrological extremes; Projected changes in hydrological extremes; Downscaling of hydrological extremes; Early warning and forecasting systems for drought and flood; Interconnections of hydrological extremes; Applicability of satellite data for hydrological studies.

Keywords

rainfall --- monsoon --- high resolution --- TRMM --- drought prediction --- APCC Multi-Model Ensemble --- seasonal climate forecast --- machine learning --- sparse monitoring network --- Fiji --- drought analysis --- ANN model --- drought indices --- meteorological drought --- SIAP --- SWSI --- hydrological drought --- discrete wavelet --- global warming --- statistical downscaling --- HBV model --- flow regime --- uncertainty --- reservoir inflow forecasting --- artificial neural network --- wavelet artificial neural network --- weighted mean analogue --- variation analogue --- streamflow --- artificial neural network --- simulation --- forecasting --- support vector machine --- evolutionary strategy --- heavy storm --- hyetograph --- temperature --- clausius-clapeyron scaling --- climate change --- the Cauca River --- climate variability --- ENSO --- extreme rainfall --- trends --- statistical downscaling --- random forest --- least square support vector regression --- extreme rainfall --- polynomial normal transform --- multivariate modeling --- sampling errors --- non-normality --- extreme rainfall analysis --- statistical analysis --- hydrological extremes --- stretched Gaussian distribution --- Hurst exponent --- INDC pledge --- precipitation --- extreme events --- extreme precipitation exposure --- non-stationary --- extreme value theory --- uncertainty --- flood regime --- flood management --- Kabul river basin --- Pakistan --- extreme events --- innovative methods --- downscaling --- forecasting --- compound events --- satellite data

Sustainability of Fossil Fuels

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ISBN: 9783039212194 / 9783039212200 Year: Pages: 284 DOI: 10.3390/books978-3-03921-220-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
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The energy and fuel industries represent an extensive field for the development and implementation of solutions aimed at improving the technological, environmental, and economic performance of technological cycles. In recent years, the issues of ecology and energy security have become especially important. Energy is firmly connected with all spheres of human economic life but, unfortunately, it also has an extremely negative (often fatal) effect on the environment and public health. Depletion of energy resources, the complexity of their extraction, and transportation are also problems of a global scale. Therefore, it is especially important nowadays to try to take care of nature and think about the resources that are necessary for future generations. For scientific teams in different countries, the development of sustainable and safe technologies for the use of fuels in the energy sector will be a challenge in the coming decades

Keywords

coal --- slurry fuel --- combustion --- forest fuels --- biomass --- anthropogenic emission concentration --- municipal solid waste --- coal processing waste --- oil refining waste --- waste management --- composite fuel --- energy production --- fuel activation --- waste-derived fuel --- coal-water slurry --- laser pulse --- syngas --- aerosol --- two-component droplet --- heating --- evaporation --- explosive breakup --- disintegration --- droplet holder material --- hydraulic fracturing --- water retention in shale --- anionic surfactant --- shale gas --- supercritical CO2 --- tectonic coal --- pore structure --- methane desorption --- embedded discrete fracture model --- fractured reservoir simulation --- matrix-fracture transmissibility --- combustion --- methane hydrate --- hydrate dissociation --- PTV method --- transport of tracers --- linear drift effect --- convection–diffusion equation --- enhanced oil recovery --- closed-form analytical solution --- methane --- combustion mechanism --- mechanism reduction --- skeletal mechanism --- Bunsen burner --- covert fault zone --- genetic mechanism --- Qikou Sag --- structure evolution --- oil-controlling mode --- Riedel shear --- Mohr–Coulomb theory --- slurry fuel --- ignition --- combustion --- combustion chamber --- soaring of fuel droplets --- trajectories of fuel droplets --- decorated polyacrylamide --- physical properties --- displacement mechanism --- flow behavior --- enhanced recovery --- injection mode --- coal consumption forecasting --- support vector machine --- improved gravitational search algorithm --- grey relational analysis --- dual string completion --- gas lift --- gas lift rate --- split factor --- gas robbing --- gas lift optimization

Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing

Authors: ---
ISBN: 9783039212156 / 9783039212163 Year: Pages: 438 DOI: 10.3390/books978-3-03921-216-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Mechanical Engineering
Added to DOAB on : 2019-12-09 11:49:15
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As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.

Keywords

landslide --- bagging ensemble --- Logistic Model Trees --- GIS --- Vietnam --- colorization --- random forest regression --- grayscale aerial image --- change detection --- gully erosion --- environmental variables --- data mining techniques --- SCAI --- GIS --- mapping --- single-class data descriptors --- materia medica resource --- Panax notoginseng --- one-class classifiers --- geoherb --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- remote sensing image segmentation --- convolutional neural networks --- Gaofen-2 --- hybrid structure convolutional neural networks --- winter wheat spatial distribution --- classification-based learning --- real-time precise point positioning --- convergence time --- ionospheric delay constraints --- precise weighting --- landslide --- weights of evidence --- logistic regression --- random forest --- hybrid model --- traffic CO --- traffic CO prediction --- neural networks --- GIS --- land use/land cover (LULC) --- unmanned aerial vehicle --- texture --- gray-level co-occurrence matrix --- machine learning --- crop --- landslide susceptibility --- random forest --- boosted regression tree --- information gain --- landslide susceptibility map --- ALS point cloud --- multi-scale --- classification --- large scene --- coarse particle --- particulate matter 10 (PM10) --- landsat image --- machine learning --- support vector machine --- high-resolution --- optical remote sensing --- object detection --- deep learning --- transfer learning --- land subsidence --- Bayes net --- naïve Bayes --- logistic --- multilayer perceptron --- logit boost --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- leaf area index (LAI) --- machine learning --- Sentinel-2 --- sensitivity analysis --- training sample size --- spectral bands --- spatial sparse recovery --- constrained spatial smoothing --- spatial spline regression --- alternating direction method of multipliers --- landslide prediction --- machine learning --- neural networks --- model switching --- spatial predictive models --- predictive accuracy --- model assessment --- variable selection --- feature selection --- model validation --- spatial predictions --- reproducible research --- Qaidam Basin --- remote sensing --- TRMM --- artificial neural network --- n/a

Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)

Authors: ---
ISBN: 9783039213757 / 9783039213764 Year: Pages: 344 DOI: 10.3390/books978-3-03921-376-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR

Keywords

Vehicle-to-X communications --- Intelligent Transport Systems --- VANET --- DSRC --- Geobroadcast --- multi-sensor --- fusion --- deep learning --- LiDAR --- camera --- ADAS --- object tracking --- kernel based MIL algorithm --- Gaussian kernel --- adaptive classifier updating --- perception in challenging conditions --- obstacle detection and classification --- dynamic path-planning algorithms --- joystick --- two-wheeled --- terrestrial vehicle --- path planning --- infinity norm --- p-norm --- kinematic control --- navigation --- actuation systems --- maneuver algorithm --- automated driving --- cooperative systems --- communications --- interface --- automated-manual transition --- driver monitoring --- visual tracking --- discriminative correlation filter bank --- occlusion --- sub-region --- global region --- autonomous vehicles --- driving decision-making model --- the emergency situations --- red light-running behaviors --- ethical and legal factors --- T-S fuzzy neural network --- road lane detection --- map generation --- driving assistance --- autonomous driving --- real-time object detection --- autonomous driving assistance system --- urban object detector --- convolutional neural networks --- machine vision --- biological vision --- deep learning --- convolutional neural network --- Gabor convolution kernel --- recurrent neural network --- enhanced learning --- autonomous vehicle --- crash injury severity prediction --- support vector machine model --- emergency decisions --- relative speed --- total vehicle mass of the front vehicle --- perception in challenging conditions --- obstacle detection and classification --- dynamic path-planning algorithms --- drowsiness detection --- smart band --- electrocardiogram (ECG) --- photoplethysmogram (PPG) --- recurrence plot (RP) --- convolutional neural network (CNN) --- squeeze-and-excitation --- residual learning --- depthwise separable convolution --- blind spot detection --- machine learning --- neural networks --- predictive --- vehicle dynamics --- electric vehicles --- FPGA --- GPU --- parallel architectures --- optimization --- panoramic image dataset --- road scene --- object detection --- deep learning --- convolutional neural network --- driverless --- autopilot --- deep leaning --- object detection --- generative adversarial nets --- image inpainting --- n/a

Symmetry in Engineering Sciences

Authors: ---
ISBN: 9783039218745 / 9783039218752 Year: Pages: 220 DOI: 10.3390/books978-3-03921-875-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:16
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This book presents interesting samples of theoretical and practical advances of symmetry in multidisciplinary engineering applications. It covers several applications, such as accessibility and traffic congestion management, path planning for mobile robots, analysis of shipment service networks, fault diagnosis methods in electrical circuits and electrical machines, geometrical issues in architecture, geometric modeling and virtual reconstruction, design of noise detectors, filters, and segmentation methods for image processing, and cyclic symmetric structures in turbomachinery applications, to name but a few. The contributions included in this book depict the state of the art in this field and lay the foundation for the possibilities that the study of symmetry has in multidisciplinary applications in the field of engineering.

Keywords

express shipment --- service network design --- linearization technique --- railway network --- path planning --- mobile robot --- environmental modeling --- optimization criteria --- path search --- aged --- high order urban hospitals (HOUHs) --- accessibility --- evaluation model --- trip impedance based on public transportation --- urban traffic planning --- 3D slicer --- classification --- extension --- random forest --- segmentation --- sensitivity analysis --- support vector machine --- tumor --- thin-walled gear --- ring damper --- vibration --- energy dissipation --- friction damping --- fault diagnosis --- lifting wavelet --- local preserving projection --- Fisher linear discriminant analysis --- semi-supervised random forest --- adaptive threshold --- clustering --- edge preserving --- noise detector --- random value impulse noise --- weighted mean filter --- anomaly detection --- local data features --- BP neural network --- local monotonicity --- convexity/concavity --- local inflection --- peaks distribution --- inclined plane --- Coalbrookdale (Shropshire) --- Agustín de Betancourt --- geometric modeling --- virtual reconstruction --- industrial heritage --- industrial archaeology --- symmetry --- rampant arch --- geometry --- optimum --- flying buttresses --- cathedral --- rolling bearings --- fault diagnosis --- broad learning model --- variational mode decomposition --- Hilbert transform --- railway transportation --- time-space network --- A* algorithm --- traffic congestion --- traffic forecasting --- traffic control --- railcar flow distribution --- asymmetry --- synchronization --- topology --- electrical circuits --- electronic devices --- mechanical structures --- robots --- graphic modelling --- complex networks --- optimization --- computing applications --- feature selection --- conditional mutual information --- feature interaction --- classification --- computer engineering

Sustainable Energy Systems Planning, Integration and Management

Authors: --- --- --- --- et al.
ISBN: 9783039280469 / 9783039280476 Year: Pages: 286 DOI: 10.3390/books978-3-03928-047-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: General and Civil Engineering --- Technology (General)
Added to DOAB on : 2020-01-30 16:39:46
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Energy systems worldwide are undergoing major transformation as a consequence of the transition towards the widespread use of clean and sustainable energy sources. Basically, this involves massive changes in technical and organizational levels together with tremendous technological upgrades in different sectors ranging from energy generation and transmission systems down to distribution systems. These actions generate huge science and engineering challenges and demands for expert knowledge in the field to create solutions for a sustainable energy system that is economically, environmentally, and socially viable while meeting high security requirements. This book covers these promising and dynamic areas of research and development, and presents contributions in sustainable energy systems planning, integration, and management. Moreover, the book elaborates on a variety of topics, ranging from design and planning of small- to large-scale energy systems to the operation and control of energy networks in different sectors, namely electricity, heat, ?and transport.

Keywords

Black Sea --- Romanian coastal environment --- wave energy --- numerical models --- SWAN --- renewable energy --- environment --- solid waste to energy plant --- FANP --- TOPSIS --- fuzzy logic --- MCDM --- smart logistics system --- smart box --- information platform --- renewable biomass energy --- agricultural pruning --- cuckoo search algorithm --- support vector machine --- ensemble empirical mode decomposition --- wind speed forecasting --- forecasting validity --- smart logistics system --- information platform --- pruning biomass --- performance evaluation --- product quality model --- product usability testing --- rural residential building --- solar energy --- heat transfer --- wind velocities --- field test and numerical simulation --- renewable energy --- load regulation --- datacenter --- smart grid --- demand response --- threshold value of daily operation hours --- intermittent heating --- configurations of internal wall --- heat storage and release --- hot summer and cold winter climate zone --- dual robust optimization --- risk aversion --- energy and environmental systems --- vehicular emissions --- multiple uncertainties --- photovoltaic systems --- meteorological variables --- electric power --- gradient descent --- sustainable development --- optimal chiller loading (OCL) --- uncertain cooling demand --- information gap decision theory (IGDT) --- mixed-integer non-linear programming problem (MINLP) --- novel method --- internal coverings --- neural networks --- energy --- thermal comfort --- control system --- resampling --- feature extraction --- non-intrusive load monitoring --- pure electric buses --- multi-type bus operating organization --- time-space network --- energy consumption --- public transport --- n/a

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