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  • machine learning  (603)
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  • 11
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    High Voltage Engineering and Applications (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: This book is a collection of recent publications from researchers all over the globe in the broad area of high-voltage engineering. The presented research papers cover both experimental and simulation studies, with a focus on topics related to insulation monitoring using state-of-the-art sensors and advanced machine learning algorithms. Special attention was given in the Special Issue to partial discharge monitoring as one of the most important techniques in insulation condition assessment. Moreover, this Special Issue contains several articles which focus on different modeling techniques that help researchers to better evaluate the condition of insulation systems. Different power system assets are addressed in this book, including transformers, outdoor insulators, underground cables, and gas-insulated substations.
    Schlagwort(e): TA1-2040 ; T1-995 ; artificial neural network ; simulation ; high-frequency ; artificial flashover tests ; wide bandgap power modules ; tracking ; electrical field strength ; fast-rise square wave voltages ; FDTD simulation ; cable joint ; corona discharge ; feature selection ; post insulator ; earthing systems ; wind speed ; surface discharge ; oil/paper insulation ; oil-paper insulation ; high-magnitude currents and impulse polarity ; UFVM ; Tettex 9520 ; electrical tree ; flashover characteristics ; composite insulator ; partial discharge ; numerical modeling ; saline mechanism ; thermal parameters ; space charge density ; seasonal ; ion flow field ; denoising ; DDX 9121b ; temperature ; transformer asset management ; cavity discharge ; space/interface charge ; insulation health index ; heat transfer model ; leakage current ; machine learning ; partial discharges (PD) ; RF signal ; flashover ; high impulse conditions ; grounding electrodes ; generalized finite difference time domain ; curve fitting ; grounding ; plasma discharge ; outdoor insulators ; flashover dynamic model ; wavelet transform ; degradation ; thermal properties ; bipolar charge transport model ; UHF sensor ; cable ; random walk theory ; tracking test setup ; GIL ; pressure ; modelling ; non-uniform pollution between windward and leeward sides ; calibrator ; secondary arc ; polymeric insulation ; optical-UHF integrated detection ; shoreline ; dry band arcing ; photoelectric fusion pattern ; DDX 8003 ; XLPE ; silicone gel ; partial discharge modeling ; electric field analysis ; NSCT ; electrode’s geometry ; gas ; Comsol Multiphysics ; fast-impulses ; laying modes ; ageing ; cable ampacity ; residual resistance formulation ; finite element analysis ; thermal effect ; hydrophobicity ; soil resistivity ; charge simulation method ; short-circuit discharge ; dry band formation ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Sprache: Englisch
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  • 12
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    Sensors in Agriculture (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.
    Schlagwort(e): TA1-2040 ; T1-995 ; optical sensor ; spectral analysis ; response surface sampling ; sensor evaluation ; electromagnetic induction ; multivariate water quality parameters ; mandarin orange ; crop inspection platform ; SPA-MLR ; object tracking ; feature selection ; simultaneous measurement ; diseases ; genetic algorithms ; processing of sensed data ; electrochemical sensors ; thermal image ; ECa-directed soil sampling ; handheld ; recognition patterns ; salt concentration ; clover-grass ; bovine embedded hardware ; weed control ; soil ; field crops ; vineyard ; connected dominating set ; water depth sensors ; SS-OCT ; wheat ; striped stem-borer ; silage ; geostatistics ; detection ; NIR hyperspectral imaging ; electronic nose ; machine learning ; virtual organizations of agents ; packing density ; data validation and calibration ; dataset ; Wi-SUN ; temperature sensors ; geoinformatics ; gas sensor ; X-ray fluorescence spectroscopy ; vegetable oil ; photograph-grid method ; Vitis vinifera ; WSN distribution algorithms ; laser-induced breakdown spectroscopy ; irrigation ; quality assessment ; energy efficiency ; wireless sensor network (WSN) ; geo-information ; Fusarium ; texture features ; weeds ; discrimination ; big data ; soil moisture sensors ; meat spoilage ; land cover ; stereo imaging ; near infrared sensors ; biological sensing ; compound sensor ; pest management ; moisture ; plant localization ; heavy metal contamination ; artificial neural networks ; spectral pre-processing ; moisture content ; apparent soil electrical conductivity ; data fusion ; semi-arid regions ; smart irrigation ; back propagation model ; wireless sensor network ; energy balance ; light-beam ; fluorescent measurement ; agriculture ; precision agriculture ; deep learning ; spectroscopy ; hulled barely ; dielectric probe ; RPAS ; water supply network ; rice leaves ; mobile app ; gradient boosted machines ; hyperspectral camera ; one-class ; nitrogen ; LiDAR ; total carbon ; chemometrics analysis ; rice ; agricultural land ; on-line vis-NIR measurement ; CARS ; obstacle detection ; stratification ; neural networks ; regression estimator ; Kinect ; proximity sensing ; distributed systems ; pest ; noninvasive detection ; texture feature ; soil mapping ; classification ; soil salinity ; visible and near-infrared reflectance spectroscopy ; germination ; computer vision ; hyperspectral imaging ; diffusion ; dielectric dispersion ; UAS ; random forests ; case studies ; total nitrogen ; thermal imaging ; cameras ; dry matter composition ; near-infrared ; salt tolerance ; deep convolutional neural networks ; soil type classification ; water management ; preprocessing methods ; wireless sensor networks (WSN) ; remote sensing image classification ; precision plant protection ; radar ; spatial variability ; GF-1 satellite ; plant disease ; naked barley ; leaf area index ; CIE-Lab ; change of support ; radiative transfer model ; 3D reconstruction ; plant phenotyping ; vine ; near infrared ; vegetation indices ; remote sensing ; greenhouse ; time-series data ; scattering ; sensor ; crop area ; speckle ; spatial data ; grapevine breeding ; wide field view ; partial least squares-discriminant analysis ; spiking ; area frame sampling ; chromium content ; machine-learning ; RGB-D sensor ; pest scouting ; PLS ; Capsicum annuum ; spatial-temporal model ; drying temperature ; boron tolerance ; ambient intelligence ; laser wavelength ; fuzzy logic ; dynamic weight ; landslide ; management zones ; real-time processing ; event detection ; crop monitoring ; apple shelf-life ; rice field monitoring ; wireless sensor ; birth sensor ; proximal sensor ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Sprache: Englisch
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  • 13
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    Shape Memory Alloys for Civil Engineering (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: This overview of the most recent advances in the field of SMA research and applications in civil engineering aims to help remove the knowledge barriers across disciplines and sheds considerable light on the opportunity to commercialize SMA products in the construction industry.
    Schlagwort(e): seismic analysis ; rocking pier ; shape memory alloy ; ECC material ; bridge engineering ; television transmission tower ; seismic excitation ; shape memory alloy damper ; parametric study ; vibration control ; shape memory alloys ; engineered cementitious composites ; composites materials ; self-recovery capacity ; bending behavior ; machine learning ; artificial neural networks ; superelastic ; parameter identification ; constitutive model ; thermodynamic parameters ; shape memory alloy (SMA) ; self-centering SMA brace ; loading rate ; initial strain ; energy dissipation coefficient ; self-centering ; beam-column joints ; seismic performance ; iron-based shape memory alloy (Fe-SMA) ; shape memory effect ; martensitic transformation ; prestressing ; low cycle fatigue ; seismic ; damping ; transmission tower ; wind excitation ; SMA damper ; energy response ; viscoelastic ; brace ; hybrid control ; seismic resilience ; self-centering rocking (SCR) piers ; seismic fragility ; resilience ; life-cycle loss ; ferrous shape memory alloys ; prestress ; recovery stress ; relaxation ; thermomechanical behavior ; fatigue ; active materials ; low-cost SMAs ; civil engineering applications ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TN Civil engineering, surveying and building::TNK Building construction and materials::TNKX Conservation of buildings and building materials
    Sprache: Englisch
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  • 14
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    Challenges and Opportunities in Applied System Innovation (2022)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: This book introduces and provides solutions to a variety of problems faced by society, companies and individuals in a quickly changing and technology-dependent world. The wide acceptance of artificial intelligence, the upcoming fourth industrial revolution and newly designed 6G technologies are seen as the main enablers and game changers in this environment. The book considers these issues not only from a technological viewpoint but also on how society, labor and the economy are affected, leading to a circular economy that affects the way people design, function and deploy complex systems.
    Schlagwort(e): Industry 4.0 ; cognitive manufacturing ; cognitive load ; human–computer interaction ; 6GIIoE priorities ; 6GIIoE challenges ; 6GIIoE applications ; information system ; sequential methodology ; 6GIIoE theoretical framework ; circular economy ; circular building ; implementation strategies ; design strategies ; circular resource flows ; digital twin ; digital model ; system optimization ; predictive maintenance ; artificial and human intelligence ; security ; risks and risk management ; quality of life ; common welfare ; socio-political assessment ; assembly ; process planning systems ; concurrent engineering ; automotive industry applications ; manufacturing industry applications ; artificial intelligence ; sustainable development ; construction ; civil engineering ; machine learning ; construction engineering ; cognitive data intelligence ; cognitive healthcare ; tiny machine learning ; 6GCIoHE theoretical framework ; data science ; statistical data processing ; predictive analytics ; classification ; clustering ; labor productivity ; health management ; health-saving strategies ; electric power industry ; bridge ; expansion joint ; joint gap ; smart bridge maintenance equipment ; sensor ; structural health monitoring ; line-scan camera ; machine vision ; change management ; COVID-19 ; decision-support model ; digitization ; employee motivation ; employee satisfaction ; human resources ; software tool ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology
    Sprache: Englisch
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  • 15
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    Green, Energy-Efficient and Sustainable Networks (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: The book Green, Energy-Efficient and Sustainable Networks provides insights and solutions for a range of problems in the field of obtaining greener, energy-efficient, and sustainable networks. The book contains the outcomes of the Special Issue on “Green, Energy-Efficient and Sustainable Networks” of the Sensors journal. Seventeen high-quality papers published in the Special Issue have been collected and reproduced in this book, demonstrating significant achievements in the field. Among the published papers, one paper is an editorial and one is a review, while the remaining 15 works are research articles. The published papers are self-contained peer-reviewed scientific works that are authored by more than 75 different contributors with both academic and industry backgrounds. The editorial paper gives an introduction to the problem of information and communication technology (ICT) energy consumption and greenhouse gas emissions, presenting the state of the art and future trends in terms of improving the energy-efficiency of wireless networks and data centers, as the major energy consumers in the ICT sector. In addition, the published articles aim to improve energy efficiency in the fields of software-defined networking, Internet of things, machine learning, authentication, energy harvesting, wireless relay systems, routing metrics, wireless sensor networks, device-to-device communications, heterogeneous wireless networks, and image sensing. The last paper is a review that gives a detailed overview of energy-efficiency improvements and methods for the implementation of fifth-generation networks and beyond. This book can serve as a source of information in industrial, teaching, and/or research and development activities. The book is a valuable source of information, since it presents recent advances in different fields related to greening and improving the energy-efficiency and sustainability of those ICTs particularly addressed in this book
    Schlagwort(e): TA1-2040 ; T1-995 ; node speed ; linear recovery ; resource block allocation ; social awareness ; internet-of-things ; scheduling algorithm ; renewables ; neural network ; battery capacity ; energy awareness ; measurement structure ; optimization ; energy efficiency ; charging efficiency ; random structural matrices ; SDN ; water filling algorithm ; ONOS ; energy harvesting ; malware detection ; node density ; HetNets ; sustainability ; cooperative smart community ; adversarial samples ; spatial modulation ; NOMA ; 5G ; light-weight authentication ; green networking ; Device-to-Device (D2D) ; lightweight cipher ; mobile edge computing ; wireless power transfer ; adaptive link rate ; successive interference cancellation (SIC) ; directional charging vehicle ; self-interference cancellation ; proportional rate constraint ; inter-meeting time ; sustainable ; RWSN ; channel state information ; stochastic geometry ; networks ; green internet of things (IoT) ; PHY-layer ; IoT ; Markov chain ; traffic engineering ; QoS ; energy-efficient Ethernet ; power ; lightweight authentication ; energy aware routing ; authentication ; wired access ; amplify-and-forward ; software defined networking (SDN) ; image compressive sensing (CS) ; green ; edge computing ; LTE-A ; opportunistic networks ; RF Fingerprinting ; data centre ; multiple-input multiple-output ; Internet of Things ; machine learning ; peer discovery ; full-duplex ; industrial ; carbon footprint ; WSN ; imperfect CSI ; data center ; symbol error probability ; physical-layer authentication ; interference coordination ; clustering ; control and data plane ; wireless ; ICT ; bisection based optimal power allocation ; energy-efficiency ; consumer preferences ; real-time traffic ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Sprache: Englisch
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  • 16
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    Applications of Remote Image Capture System in Agriculture (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering.
    Schlagwort(e): SVM ; budding rate ; UAV ; geometric consistency ; radiometric consistency ; point clouds ; ICP ; reflectance maps ; vegetation indices ; Parrot Sequoia ; artificial intelligence ; precision agriculture ; agricultural robot ; optimization algorithm ; online operation ; segmentation ; coffee leaf rust ; machine learning ; deep learning ; remote sensing ; Fourth Industrial Revolution ; Agriculture 4.0 ; failure strain ; sandstone ; digital image correlation ; Hill–Tsai failure criterion ; finite element method ; reference evapotranspiration ; moisture sensors ; machine learning regression ; frequency-domain reflectometry ; randomizable filtered classifier ; convolutional neural network ; U-Net ; land use ; banana plantation ; Panama TR4 ; aerial photography ; remote images ; systematic mapping study ; agriculture ; applications ; total leaf area ; mixed pixels ; Cabernet Sauvignon ; NDVI ; Normalized Difference Vegetation Index ; precision viticulture ; 3D model ; spatial vision ; fertirrigation ; teaching–learning ; spectrometry ; Sentinel-2 ; pasture quality index ; normalized difference vegetation index ; normalized difference water index ; supplementation ; decision making ; digital agriculture ; grape yield estimate ; berries counting ; Dilated CNN ; machine learning algorithms ; classification performance ; winter wheat mapping ; large-scale ; water stress ; Prunus avium L. ; stem water potential ; low-cost thermography ; thermal indexes ; canopy temperature ; non-water-stressed baselines ; non-transpiration baseline ; soil moisture ; andosols ; image processing ; greenhouse ; automatic tomato harvesting ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Sprache: Englisch
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  • 17
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    Advances in Transportation Meteorology (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: Transportation is one of the most crucial aspects across the world, supporting the daily life of human beings and the sustainable development of the whole of society. Generally, meteorology causes various impacts on transportation operation, safety and efficiency. In the context of global warming, increasing numbers of extreme weather and climate events (such as fog, icy roads, and extreme winds) have been detected worldwide and are expected to occur more frequently in the future. Meanwhile, extreme events, such as dense fog, rainstorm, and blizzard, tend to damage transportation and traffic facilities (such as express ways, port, airport, and high-speed railway) and induce serious traffic blocks and accidents. In recent decades, concentrated and continuous efforts have been made to carry out meteorological analyses regardless of urban traffic or transportation conditions, including those of highways, shipping, aviation, etc. A number of methods and techniques have been intensively developed to promote the qualities of both observations and forecasts. More recently, state-of-the-art machine learning frameworks have also been widely introduced into studies regarding transportation meteorology and many other fields.
    Schlagwort(e): transportation meteorology ; pavement temperature prediction ; deep learning ; BiLSTM ; attention mechanisms ; winter icing ; air pollution ; traffic vitality ; built environment ; spatial correlation ; spatial lag model ; phone signaling data ; air quality ; behavioral habits ; activity density ; population distribution ; land use mix ; wind forecast ; error decomposition ; bias ; distribution ; sequence ; urban meteorology ; observation ; forecast ; early warning ; review ; China ; low-level wind shear ; ensemble learning classifiers ; Bayesian optimization ; SHapley Additive exPlanations ; wind shear ; go-around ; machine learning ; dynamic ensemble selection ; civil aviation safety ; pilot reports ; self-paced ensemble ; Shapley additive explanations ; climate change ; climatology ; sea ice ; marginal sea ; East Asia ; time-series modeling ; pavement temperature ; nowcasting ; variation characteristics ; forecast validation ; relative humidity ; microwave radiometer data ; total rainfall ; precipitation duration ; vertical distribution ; Beijing–Tianjin–Hebei region ; rail breakage ; frequency ; high-speed railway ; Siberian high ; teleconnection ; temperature ; Qinling mountains ; rainfall ; change characteristics ; geographical factors ; highways ; road blockage ; fuzzy analytic hierarchy process ; CRITIC weight assignment method ; road network vulnerability ; spatiotemporal distribution ; precipitation forecast ; ConvLSTM ; PredRNN ; expressway ; agglomerate fog ; risk level prediction of fog-related accidents ; meteorological conditions ; road hidden dangers ; traffic flow conditions ; visibility ; Yellow Sea and Bohai Sea ; observation data ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TR Transport technology and trades
    Sprache: Englisch
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  • 18
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    Mechanical Properties of Polymeric, Metallic, and Composite Materials (2023)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: There has been significant growth in branches of industry directly related to new materials, such as metals, polymers, and composite materials. Considering the increase in material costs, it has become exceedingly important to produce lightweight constructions through the use of certified materials with appropriate mechanical properties. Many composite materials, especially in building engineering, are characterized by the use of waste materials, allowing them to meet environmental demands and often also positively affecting the performance (as well as mechanical) properties of the whole construction. A similar phenomenon has been noticed in polymers and metals, with the “ecologically friendly” factor having increasing influence in such materials. The main aim of our Special Issue was to gather novel research results concerning different materials available for all important industries—building engineering, the heavy industry, automotive, aerospace, and medicine. Such a general title has been proposed to also include different manufacturing technologies using various materials—conventional (milling, casting, forming, and turning) and novel (hybrid and additive manufacturing).
    Schlagwort(e): additive manufacturing ; powder bed fusion ; 316L stainless steel ; ultrasonic atomization ; gas atomization ; three-point bending ; polyamide-based composites ; fused filament fabrication ; concrete additives ; concrete fibers ; concrete strength tests ; threshold effect ; flake graphene ; graphene oxide ; reduced graphene oxide ; lubricants ; grease ; fatigue life prediction ; CuZn37 brass ; machine learning ; IPCs ; ceramic preform ; ceramic–elastomer composite ; silane coupling agent ; hot isostatic pressing (HIP) ; wettability ; mechanical properties ; mechanical engineering ; laser powder bed fusion ; 21 NiCrMo2 steel ; process parameters ; post-heat treatment ; torsional strength ; cellular structures ; 20MnCr5 Steel ; cement–glass composite bricks ; digital image correlation analysis ; material extrusion ; PET-G ; waste disposal ; hybrid additive manufacturing ; lattice structures ; hot isostatic pressing ; fatigue behaviour ; polymer–straw boards ; thermoplastic polymers ; annual plants ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
    Sprache: Englisch
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  • 19
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    Overcoming Data Scarcity in Earth Science (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.
    Schlagwort(e): TA1-2040 ; T1-995 ; TA170-171 ; geophysical monitoring ; data scarcity ; missing data ; climate extreme indices (CEIs) ; rule extraction ; Dataset Licensedatabase ; data assimilation ; data imputation ; support vector machines ; environmental observations ; multi-class classification ; earth-science data ; remote sensing ; magnetotelluric monitoring ; soil texture calculator ; machine learning ; ClimPACT ; invasive species ; species distribution modeling ; 3D-Var ; ensemble learning ; data quality ; water quality ; microhabitat ; k-Nearest Neighbors ; Expert Team on Climate Change Detection and Indices (ETCCDI) ; decision trees ; processing ; attribute reduction ; Expert Team on Sector-specific Climate Indices (ET-SCI) ; core attribute ; rough set theory ; GLDAS ; arthropod vector ; environmental modeling ; statistical methods ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Sprache: Englisch
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  • 20
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    Machining Dynamics and Parameters Process Optimization (2021)
    MDPI - Multidisciplinary Digital Publishing Institute
    Details
    Publikationsdatum: 2024-04-11
    Beschreibung: As we move further into the 21st century, despite the fact that new technologies have emerged, machining remains the key operation to achieve high productivity and precision for high-added value parts in several sectors, but recent advances in computer applications should close the gap between simulations and industrial practices. This book, “Machining Dynamics and Parameters Process Optimization”, is oriented toward the different strategies and paths when it comes to increasing productivity and reliability in metal removal processes. The topics include the dynamic characterization of machine tools, experimental dampening techniques, and optimization algorithms combined with signal monitoring.
    Schlagwort(e): CNC parameters ; machining mode ; high speed ; high accuracy ; high surface quality ; five-axis linear-segment toolpath ; path smoothing ; B-spline curve-fitting ; path synchronization ; feedrate scheduling ; flute-grinding ; evolution algorithms ; wheel location and orientation ; thin-floor machining ; chatter ; magnetorheological damper ; bull-nose end mill ; tool wear monitoring ; milling ; complex part ; deep learning ; autoencoder ; deep multi-layer perceptron ; tool condition monitoring ; tool change policy ; Industry 4.0 ; machine learning ; CNN ; AI ; additive manufacturing ; thin walled machining ; dynamics ; machining cycle optimization ; multivariable tool ; stable peninsula ; homotopy perturbation method ; machining robot ; natural frequency prediction ; model optimization ; dynamic performance ; stability ; machining ; grinding ; n/a ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Sprache: Englisch
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