Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Computational Optimizations for Machine Learning
| Computational Optimizations for Machine Learning |
| Autore | Gabbay Freddy |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (276 p.) |
| Soggetto topico |
Mathematics & science
Research & information: general |
| Soggetto non controllato |
ARIMA model
artificial intelligence autoencoders bed roughness bio-inspired algorithms CNN architecture computational intelligence convolutional neural network deep compression deep learning deep neural networks DNN energy dissipation evolution of weights evolutionary algorithms evolutionary computation feature selection floating-point numbers FLOW-3D generalization error genetic algorithms hardware acceleration Heating, Ventilation and Air Conditioning (HVAC) hydraulic jumps low power machine learning meta-heuristic optimization metaheuristics search model predictive control multi-objective optimization nature inspired algorithms neural networks nonlinear systems online model selection online optimization precipitation nowcasting quantization radar data recurrent neural networks ReLU sensitivity analysis smart building soft computing swarm intelligence time series analysis training |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557610303321 |
Gabbay Freddy
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Structural Prognostics and Health Management in Power & Energy Systems
| Structural Prognostics and Health Management in Power & Energy Systems |
| Autore | Wang Dong |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (218 p.) |
| Soggetto topico | Philosophy |
| Soggetto non controllato |
analysis mode decomposition
analysis-empirical mode decomposition data-driven deep learning DNN dynamic analysis dynamic analysis of the structure dynamic fuzzy reliability analysis empirical mode decomposition extremum surface response method fault detection full-scale static test fuzzy safety criterion health monitoring lateral-river vibration life cycle cost lithium-ion battery low frequency tail fluctuation machine learning mode mixing multioperation condition NAR neural network neural networks non-probabilistic reliability index offshore structures offshore wind turbines oil and gas platforms operational modal analysis optimized deep belief networks probabilistic analyses of stochastic processes and frequency prognostic and Health Management prognostics regeneration phenomenon reliability remaining useful life renewable energy residual useful life retrofitting activities rotation of hydraulic generator sensitivity analysis sifting stop criterion similarity-based approach stochastic subspace identification strain prediction structural health monitoring supervisory control and data acquisition system supporting vector machine (SVM) techno-economic assessments turbine blisk underground powerhouse vertical axis wind turbine vibration test vibration transmission mechanism wave-structure interaction (WSI) wavelet decomposition weighted regression wind and wave analysis wind turbine blade wind turbines |
| ISBN | 3-03921-767-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910372782603321 |
|
Wang Dong
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||