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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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Time Series Modelling
| Time Series Modelling |
| Autore | Weiss Christian H |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (372 p.) |
| Soggetto topico | Humanities |
| Soggetto non controllato |
time series
anomaly detection unsupervised learning kernel density estimation missing data multivariate time series nonstationary spectral matrix local field potential electric power forecasting accuracy machine learning extended binomial distribution INAR thinning operator time series of counts unemployment rate SARIMA SETAR Holt–Winters ETS neural network autoregression Romania integer-valued time series bivariate Poisson INGARCH model outliers robust estimation minimum density power divergence estimator CUSUM control chart INAR-type time series statistical process monitoring random survival rate zero-inflation cointegration subspace algorithms VARMA models seasonality finance volatility fluctuation Student’s t-process entropy based particle filter relative entropy count data time series analysis Julia programming language ordinal patterns long-range dependence multivariate data analysis limit theorems integer-valued moving average model counting series dispersion test Bell distribution count time series estimation overdispersion multivariate count data INGACRCH state-space model bank failures transactions periodic autoregression integer-valued threshold models parameter estimation models |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557541003321 |
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Weiss Christian H
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||