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Energy and Technical Building Systems - Scientific and Technological Advances

Authors: ---
ISBN: 9783039281787 9783039281794 Year: Pages: 220 DOI: 10.3390/books978-3-03928-179-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2020-04-07 23:07:09
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Future buildings require not only energy efficiency but also proper building automation and control system functionalities in order to respond to the needs of occupants and energy grids. These development paths require a focus on occupant needs such as good indoor climate, easy operability, and monitoring. Another area to be tackled is energy flexibility, which is needed to make buildings responsive to the price signals of electricity grids with increasing amounts of fluctuating renewable energy generation installed both in central grids and at building sites. This Special Issue is dedicated to HVAC systems, load shifting, indoor climate, and energy and ventilation performance analyses in buildings. All these topics are important for improving the energy performance of new and renovated buildings within the roadmap of low energy and nearly zero energy buildings. To improve energy performance and, at the same time, occupant comfort and wellbeing, new technical solutions are required. Occupancy patterns and recognition, intelligent building management, demand response and performance of heating, cooling and ventilation systems are some common keywords in the articles of this Special Issue contributing to future highly performing buildings with reliable operation.

Keywords

ice rinks --- air distribution solutions --- indoor air temperature gradient --- air handling unit configuration --- building energy efficiency --- building performance simulation --- energy and HVAC-systems in buildings --- energy piles --- validation --- floor slab heat loss --- energy --- computer simulations --- predictive rule-based control --- hourly CO2eq. intensity --- demand response --- energy flexibility --- n/a --- indoor environment quality --- thermal comfort --- personalized ventilation --- fuzzy logic --- environmental impact --- device efficiency --- air pollutant --- multi-households --- solid oxide fuel cell cogeneration system --- end-use energy consumption --- heating --- ventilation and air conditioning (HVAC) --- intelligent system management --- lighting electrical energy --- national electricity grid --- office building --- Photovoltaic system --- simulation --- Simulink® --- deep renovation --- energy retrofit --- detached house --- multi-objective optimization --- greenhouse gas emissions --- heat pump --- genetic algorithm --- occupancy density --- moisture conditions --- energy use --- indoor air quality --- ventilation rate --- KNX --- Neural Network (NN) --- Multilayer Perceptron (MLP) --- Random Tree (RT) --- Linear Regression (LR) --- Cloud Computing (CC) --- Internet of Things (IoT) --- LMS (Least Mean Squares) Adaptive filter (AF) --- gateway --- monitoring --- occupancy --- prediction --- IBM SPSS --- Intelligent Buildings (IB) --- energy savings

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: English
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

Smart Energy Management for Smart Grids

Authors: ---
ISBN: 9783039281428 9783039281435 Year: Pages: 350 DOI: 10.3390/books978-3-03928-143-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.

Keywords

seawater pumped storage --- renewable energy --- active distribution networks --- two-stage --- scheduling --- distributed generation --- storage device --- MILP --- ToU tariff --- optimization --- daily consumption curve --- peak/off-peak --- programmable appliances --- smart grid --- smart energy --- sustainability --- values --- technology acceptance --- technology adoption --- smart grid --- Smart Grid Station --- renewable energy sources --- energy management system --- smart metering --- feedback --- households --- energy and water consumption --- theories of social practice --- smart grid --- differentiation --- development demand --- comprehensive evaluation --- energy management system --- energy storage system --- semantic web technologies --- rules --- ontology --- engineering support --- smart grid architecture model --- model driven architecture --- IEC 61850 --- IEC 61499 --- energy storage system --- electricity charge discount program --- peak reduction --- economic feasibility analysis --- policy effectiveness evaluation --- occupant behavior --- single-person household --- energy consumption --- Korean Time Use Survey --- EnergyPlus --- data mining --- K-modes clustering --- support vector machine --- Gaussian process regression --- combined dispatch (CD) strategy --- optimization --- HOMER --- net present cost (NPC) --- sensitivity analysis --- renewable energy --- solar power generation prediction --- smart grid --- photovoltaic power --- machine learning --- electrical distribution system --- graph theory --- micro grids --- heuristic --- optimization --- planning --- unbalanced three-phase distribution networks --- optimal power flows --- genetic algorithm --- holomorphic embedding load flow method --- simulation --- forecasting --- solar generation --- storage capacity --- game theory --- nash equilibrium --- distributed energy management algorithm --- micro grid --- meta heuristic techniques --- R&amp --- D planning --- patent analysis --- sustainable smart grid technology --- R&amp --- D strategy --- STEEP analysis --- scenario planning --- electric vehicle charging technology --- multilayer perceptron neural network --- support vector machine --- cyberattacks --- optimal power flow --- smart grid security --- intruder detection system

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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 (2)

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