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Advanced Process Monitoring for Industry 4.0
| Advanced Process Monitoring for Industry 4.0 |
| Autore | Reis Marco S |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (288 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
spatial-temporal data
pasting process process image convolutional neural network Industry 4.0 auto machine learning failure mode effects analysis risk priority number rolling bearing condition monitoring classification OPTICS statistical process control control chart pattern disruptions disruption management fault diagnosis construction industry plaster production neural networks decision support systems expert systems failure mode and effects analysis (FMEA) discriminant analysis non-intrusive load monitoring load identification membrane data reconciliation real-time online monitoring Six Sigma multivariate data analysis latent variables models PCA PLS high-dimensional data statistical process monitoring artificial generation of variability data augmentation quality prediction continuous casting multiscale time series classification imbalanced data combustion optical sensors spectroscopy measurements signal detection digital processing principal component analysis curve resolution data mining semiconductor manufacturing quality control yield improvement fault detection process control multi-phase residual recursive model multi-mode model process monitoring |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557491503321 |
Reis Marco S
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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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Artificial Intelligence for Smart and Sustainable Energy Systems and Applications
| Artificial Intelligence for Smart and Sustainable Energy Systems and Applications |
| Autore | Lytras Miltiadis |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (258 p.) |
| Soggetto non controllato |
artificial neural network
home energy management systems conditional random fields LR ELR energy disaggregation artificial intelligence genetic algorithm decision tree static young’s modulus price scheduling self-adaptive differential evolution algorithm Marsh funnel energy yield point non-intrusive load monitoring mud rheology distributed genetic algorithm MCP39F511 Jetson TX2 sustainable development artificial neural networks transient signature load disaggregation smart villages ambient assisted living smart cities demand side management smart city CNN wireless sensor networks object detection drill-in fluid ERELM sandstone reservoirs RPN deep learning RELM smart grids multiple kernel learning load feature extraction NILM energy management energy efficient coverage insulator Faster R-CNN home energy management smart grid LSTM smart metering optimization algorithms forecasting plastic viscosity machine learning computational intelligence policy making support vector machine internet of things sensor network nonintrusive load monitoring demand response |
| ISBN | 3-03928-890-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404078103321 |
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Lytras Miltiadis
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 |
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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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Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization
| Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization |
| Autore | Deschrijver Dirk |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (201 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
passive house
enclosure structure heat transfer coefficient energy consumption turbo-propeller regional fuel weight range design CO2 reduction multi-objective combinatorial optimization meta-heuristics ant colony optimization non-intrusive load monitoring appliance classification appliance feature recurrence graph weighted recurrence graph V-I trajectory convolutional neural network energy baselines machine learning clustering neural methods smart intelligent systems building energy consumption building load forecasting energy efficiency thermal improved of buildings anti-icing heat and mass transfer heating power distribution heat load reduction optimization method experimental validation big data process predictive maintenance fracturing roofs to maintain entry (FRME) field measurement numerical simulation side abutment pressure strata movement energy manufacturing prediction forecasting modelling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557346903321 |
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Deschrijver Dirk
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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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Sustainable Energy Systems Planning, Integration and Management
| Sustainable Energy Systems Planning, Integration and Management |
| Autore | Mohammadi-ivatloo Behnam |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (286 p.) |
| Soggetto non controllato |
Romanian coastal environment
neural networks intermittent heating wind velocities time-space network optimal chiller loading (OCL) renewable energy pure electric buses mixed-integer non-linear programming problem (MINLP) control system FANP energy consumption load regulation energy smart box novel method smart logistics system multiple uncertainties non-intrusive load monitoring wind speed forecasting solid waste to energy plant uncertain cooling demand dual robust optimization Black Sea field test and numerical simulation electric power sustainable development multi-type bus operating organization cuckoo search algorithm vehicular emissions SWAN public transport product quality model MCDM TOPSIS heat transfer solar energy forecasting validity information gap decision theory (IGDT) photovoltaic systems configurations of internal wall ensemble empirical mode decomposition agricultural pruning hot summer and cold winter climate zone energy and environmental systems feature extraction information platform pruning biomass smart grid product usability testing meteorological variables fuzzy logic performance evaluation rural residential building threshold value of daily operation hours datacenter wave energy thermal comfort heat storage and release resampling risk aversion environment support vector machine internal coverings numerical models gradient descent renewable biomass energy demand response |
| ISBN | 3-03928-047-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910372783903321 |
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Mohammadi-ivatloo Behnam
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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