Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos
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| Autore: |
Janya-anurak Chettapong
|
| Titolo: |
Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos
|
| Pubblicazione: | KIT Scientific Publishing, 2017 |
| Descrizione fisica: | 1 online resource (XIX, 210 p. p.) |
| Soggetto topico: | Computer science |
| Soggetto non controllato: | Distributed Parameter Systems |
| generalized polynomial chaos | |
| Parameter estimation | |
| ParameterschätzungUncertainty Quantification | |
| Sensitivitätsanalyse | |
| Sensitivity Analysis | |
| Unsicherheit Quantifizierung | |
| verteilt-parametrische Systeme | |
| Sommario/riassunto: | In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort. The framework using gPC based on Bayesian UQ proposed in this work is capable of analyzing the system systematically and reducing the disagreement between the model predictions and the measurements of the real processes to fulfill user defined performance criteria. |
| Titolo autorizzato: | Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos |
| ISBN: | 1-000-06694-0 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910346763703321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |