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Energy Data Analytics for Smart Meter Data
| Energy Data Analytics for Smart Meter Data |
| Autore | Reinhardt Andreas |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (346 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
smart grid
nontechnical losses electricity theft detection synthetic minority oversampling technique K-means cluster random forest smart grids smart energy system smart meter GDPR data privacy ethics multi-label learning Non-intrusive Load Monitoring appliance recognition fryze power theory V-I trajectory Convolutional Neural Network distance similarity matrix activation current electric vehicle synthetic data exponential distribution Poisson distribution Gaussian mixture models mathematical modeling machine learning simulation Non-Intrusive Load Monitoring (NILM) NILM datasets power signature electric load simulation data-driven approaches smart meters text convolutional neural networks (TextCNN) time-series classification data annotation non-intrusive load monitoring semi-automatic labeling appliance load signatures ambient influences device classification accuracy NILM signature load disaggregation transients pulse generator smart metering smart power grids power consumption data energy data processing user-centric applications of energy data convolutional neural network energy consumption energy data analytics energy disaggregation real-time smart meter data transient load signature attention mechanism deep neural network electrical energy load scheduling satisfaction Shapley Value solar photovoltaics review deep learning deep neural networks |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557645803321 |
Reinhardt Andreas
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Life Cycle Prediction and Maintenance of Buildings
| Life Cycle Prediction and Maintenance of Buildings |
| Autore | de Brito Jorge |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (256 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
energy efficiency
indoor climate quality life cycle economy changing operational environment municipal building procurement climate targets Insurance mathematical models service life prediction models natural stone claddings insurance premium risk assessment linoleum and vinyl floorings inspection pathology statistical survey healthcare infrastructures technical condition performance characteristics degree of wear service life preventive maintenance Digitization Key Performance Indicators KPIs Asset Management Facility Management Operations Maintenance & Repairs Decision Support System Facility Condition Index building construction material life cycle costs thermal insulation system conservation natural stone long-term weathered water repellents durability single-sided NMR Life Cycle Assessment uncertainties seismic hazard building renovation retrofit buildings building components building elements climate change degradation maintainability service life prediction existing structures reinforced concrete time-dependent reliability life cycle Gaussian mixture models strength degradation steel corrosion secondary databases single-family house energy supply system payback period internal rate of return energy price Swedish climate zones climate adaptation maintenance operation management |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557595003321 |
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de Brito Jorge
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Quantifying Aesthetics of Visual Design Applied to Automatic Design : Doctoral Thesis accepted by Purdue University / Ali Jahanian
| Quantifying Aesthetics of Visual Design Applied to Automatic Design : Doctoral Thesis accepted by Purdue University / Ali Jahanian |
| Autore | Jahanian, Ali |
| Pubbl/distr/stampa | Cham, : Springer, 2016 |
| Descrizione fisica | xiv, 137 p. : ill. ; 24 cm |
| Soggetto topico | 00A79 (77-XX) - Physics [MSC 2020] |
| Soggetto non controllato |
Automatic design of visual media
Design Mining Gaussian mixture models Graphical materials Latent Dirichlet Allocation Dual Topic Model Quantification of Aesthetics Quantification of Visual Design |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0169822 |
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Jahanian, Ali
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| Cham, : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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