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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: English
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

Remote Sensing for Target Object Detection and Identification

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ISBN: 9783039283323 9783039283330 Year: Pages: 336 DOI: 10.3390/books978-3-03928-333-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2020-04-07 23:07:09
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Target object detection and identification are among the primary uses for a remote sensing system. This is crucial in several fields, including environmental and urban monitoring, hazard and disaster management, and defense and military. In recent years, these analyses have used the tremendous amount of data acquired by sensors mounted on satellite, airborne, and unmanned aerial vehicle (UAV) platforms. This book promotes papers exploiting different remote sensing data for target object detection and identification, such as synthetic aperture radar (SAR) imaging and multispectral and hyperspectral imaging. Several cutting-edge contributions, which provide examples of how to select of a technology or another depending on the specific application, will be detailed.

Keywords

anomaly detection --- hyperspectral imagery --- low-rank representation --- dictionary construction --- HSI reconstruction --- sparse coding --- adaptive weighting --- infrared small target detection --- local prior analysis --- nonconvex tensor robust principle component analysis --- partial sum of the tensor nuclear norm --- low rank sparse decomposition --- Lp-norm constraint --- non-convex optimization --- alternating direction method of multipliers --- infrared small target detection --- convolutional neural networks (CNNs) --- object detection --- remote sensing images --- contextual information --- part-based --- multi-model --- very-high-resolution (VHR) remote sensing imagery --- object detection --- multi-scale pyramidal features --- multi-scale strategies --- oil tank detection --- unsupervised saliency model --- Color Markov Chain --- bottom-up and top-down --- hazard prevention --- flood hazard --- hidden danger identification --- tower failure --- vehicle detection --- object matching --- superpixel segmentation --- unmanned aerial vehicle --- remote sensing imagery --- thermal infrared target tracking --- semantic features --- mask sparse representation --- particle filter framework --- ADMM --- satellite videos --- region proposals --- convolutional neural networks --- tiny and dim target detection --- component mixture model --- object detection --- remote sensing image --- deep learning --- convolutional neural networks (CNNs) --- hardware architecture --- processor --- ground-based detection --- infrared imaging --- observability --- detecting distance --- earth entry vehicle --- synthetic aperture radar (SAR) --- rivers water-flow elevation estimation --- pixel-tracking --- phase unwrapping --- infrared small-faint target detection --- non-independent and identical distribution (non-i.i.d.) mixture of Gaussians --- flux density --- variational Bayesian --- target detection --- target identification --- SAR --- visible --- infrared --- hyperspectral

Control and Nonlinear Dynamics on Energy Conversion Systems

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ISBN: 9783039211104 9783039211111 Year: Pages: 438 DOI: 10.3390/books978-3-03921-111-1 Language: English
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 ever-increasing need for higher efficiency, smaller size, and lower cost make the analysis, understanding, and design of energy conversion systems extremely important, interesting, and even imperative. One of the most neglected features in the study of such systems is the effect of the inherent nonlinearities on the stability of the system. Due to these nonlinearities, these devices may exhibit undesirable and complex dynamics, which are the focus of many researchers. Even though a lot of research has taken place in this area during the last 20 years, it is still an active research topic for mainstream power engineers. This research has demonstrated that these systems can become unstable with a direct result in increased losses, extra subharmonics, and even uncontrollability/unobservability. The detailed study of these systems can help in the design of smaller, lighter, and less expensive converters that are particularly important in emerging areas of research like electric vehicles, smart grids, renewable energy sources, and others. The aim of this Special Issue is to cover control and nonlinear aspects of instabilities in different energy conversion systems: theoretical, analysis modelling, and practical solutions for such emerging applications. In this Special Issue, we present novel research works in different areas of the control and nonlinear dynamics of energy conversion systems.

Keywords

data-driven --- prediction --- neural network --- air-handling unit (AHU) --- supply air temperature --- pulverizing system --- soft sensor --- inferential control --- moving horizon estimation --- multi-model predictive control --- micro-grid --- droop control --- virtual impedance --- harmonic suppression --- power quality --- combined heat and power unit --- two-stage bypass --- dynamic model --- coordinated control system --- predictive control --- decoupling control --- power conversion --- model–plant mismatches --- disturbance observer --- performance recovery --- offset-free --- electrical machine --- electromagnetic vibration --- multiphysics --- rotor dynamics --- air gap eccentricity --- calculation method --- magnetic saturation --- corrugated pipe --- whistling noise --- Helmholtz number --- excited modes --- switched reluctance generator --- capacitance current pulse train control --- voltage ripple --- capacitance current --- feedback coefficient --- distributed architecture --- maximum power point tracking --- sliding mode control --- overvoltage --- permanent magnet synchronous motor (PMSM) --- single artificial neuron goal representation heuristic dynamic programming (SAN-GrHDP) --- single artificial neuron (SAN) --- reinforcement learning (RL) --- goal representation heuristic dynamic programming (GrHDP) --- adaptive dynamic programming (ADP) --- sliding mode observer (SMO) --- permanent magnet synchronous motor (PMSM) --- extended back electromotive force (EEMF) --- position sensorless --- bridgeless converter --- discontinuous conduction mode (DCM) --- high step-up voltage gain --- power factor correction (PFC) --- space mechanism --- multi-clearance --- nonlinear dynamic model --- planetary gears --- vibration characteristics --- new step-up converter --- ultrahigh voltage conversion ratio --- small-signal model --- average-current mode control --- slope compensation --- monodromy matrix --- current mode control --- boost-flyback converter --- explosion-magnetic generator --- plasma accelerator --- current-pulse formation --- DC-DC buck converter --- contraction analysis --- global stability --- matrix norm --- DC micro grid --- efficiency optimization --- variable bus voltage MG --- variable switching frequency DC-DC converters --- centralized vs. decentralized control --- local vs. global optimization --- buck converter --- DC motor --- bifurcations in control parameter --- sliding control --- zero average dynamics --- fixed-point inducting control --- DC-DC converters --- quadratic boost --- maximum power point tracking (MPPT) --- nonlinear dynamics --- subharmonic oscillations --- photovoltaic (PV) --- steel catenary riser --- rigid body rotation --- wave --- the load of suspension point in the z direction --- Cable3D

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MDPI - Multidisciplinary Digital Publishing Institute (3)


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CC by-nc-nd (3)


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english (3)


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2020 (1)

2019 (2)