Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos

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 analy...

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Main Author: Janya-anurak, Chettapong (auth)
Format: Book Chapter
Published: KIT Scientific Publishing 2017
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020 |a KSP/1000066940 
020 |a 9783731506423 
024 7 |a 10.5445/KSP/1000066940  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Janya-anurak, Chettapong  |4 auth 
245 1 0 |a Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos 
260 |b KIT Scientific Publishing  |c 2017 
300 |a 1 electronic resource (XIX, 210 p. p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a 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. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-sa/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-sa/4.0/ 
546 |a English 
653 |a ParameterschätzungUncertainty Quantification 
653 |a Parameter estimation 
653 |a verteilt-parametrische Systeme 
653 |a Sensitivity Analysis 
653 |a generalized polynomial chaos 
653 |a Distributed Parameter Systems 
653 |a Sensitivitätsanalyse 
653 |a Unsicherheit Quantifizierung 
856 4 0 |a www.oapen.org  |u https://www.ksp.kit.edu/9783731506423  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/47993  |7 0  |z DOAB: description of the publication