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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 online resource (288 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
artificial generation of variability
auto machine learning classification combustion condition monitoring construction industry continuous casting control chart pattern convolutional neural network curve resolution data augmentation data mining data reconciliation decision support systems digital processing discriminant analysis disruption management disruptions expert systems failure mode and effects analysis (FMEA) failure mode effects analysis fault detection fault diagnosis high-dimensional data imbalanced data Industry 4.0 latent variables models load identification membrane monitoring multi-mode model multi-phase residual recursive model multiscale multivariate data analysis n/a neural networks non-intrusive load monitoring online optical sensors OPTICS pasting process PCA plaster production PLS principal component analysis process control process image process monitoring quality control quality prediction real-time risk priority number rolling bearing semiconductor manufacturing signal detection Six Sigma spatial-temporal data spectroscopy measurements statistical process control statistical process monitoring time series classification yield improvement |
| 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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Big Data Analytics and Information Science for Business and Biomedical Applications
| Big Data Analytics and Information Science for Business and Biomedical Applications |
| Autore | Ahmed S. Ejaz |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (246 p.) |
| Soggetto topico |
Humanities
Social interaction |
| Soggetto non controllato |
abdominal aortic aneurysm
ant colony system asymptotic theory bayesian spatial mixture model causal and dilated convolutional neural networks deep learning DWD EEG/MEG data elastic net emulation ensembling entropy-based robust EM estimation consistency feature fusion feature representation financial time series generalized linear models high dimension high dimensional predictors high dimensional time-series high-dimensional high-dimensional data information complexity criteria inverse problem L2-consistency Lasso Medicare data missingness mechanism mixture regression model selection multicategory classification nonlocal prior nonparamteric boostrap nuisance penalty methods post-selection inference prediction proximal algorithm random subspaces regularization segmentation sparse group lasso sparse PCA stepwise regression strong selection consistency text mining trend analysis unconventional likelihood |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557614803321 |
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Ahmed S. Ejaz
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big Data Analytics and Information Science for Business and Biomedical Applications II
| Big Data Analytics and Information Science for Business and Biomedical Applications II |
| Autore | Ahmed S. Ejaz |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (196 p.) |
| Soggetto topico |
Computer science
Information technology industries |
| Soggetto non controllato |
asymptotic bias and risk
bandwidth selection Bayesian modeling big data adaptation brain network cancer causal structure learning chest X-ray images consistency correlation deep learning dividend estimation edge-preserving image denoising FCI algorithm fMRI functional connectivity functional predictor functional principal component analysis functional regression gestational weight high dimensionality high-dimensional data Human Connectome Project image sequence infant birth weight joint modeling jump regression analysis LASSO estimation linear mixed model linear mixed-effects model local smoothing longitudinal data lung diseases maternal weight gain mobile device multicollinearity network analysis nonparametric regression nonparametric testing online health community options markets PC algorithm pretest and shrinkage estimation pretrained neural networks ridge estimation social support sparse group regularization spatio-temporal data statistics transfer learning wearable device data weighted least squares |
| ISBN | 3-0365-5550-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910637784003321 |
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Ahmed S. Ejaz
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Recent Advances and Applications of Machine Learning in Metal Forming Processes
| Recent Advances and Applications of Machine Learning in Metal Forming Processes |
| Autore | Prates Pedro |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (210 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Mining technology & engineering |
| Soggetto non controllato |
sheet metal forming
uncertainty analysis metamodeling machine learning hot rolling strip edge defects intelligent recognition convolutional neural networks deep-drawing kriging metamodeling multi-objective optimization FE (Finite Element) AutoForm robust analysis defect prediction mechanical properties prediction high-dimensional data feature selection maximum information coefficient complex network clustering ring rolling process energy estimation metal forming thermo-mechanical FEM analysis artificial neural network aluminum alloy mechanical property UTS topological optimization artificial neural networks (ANN) machine learning (ML) press-brake bending air-bending three-point bending test sheet metal buckling instability oil canning artificial intelligence convolution neural network hot rolled strip steel defect classification generative adversarial network attention mechanism deep learning mechanical constitutive model finite element analysis plasticity parameter identification full-field measurements |
| ISBN | 3-0365-5772-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910637782503321 |
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Prates Pedro
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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