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

    Chettapong Janya-anurak

    Band 31 von Karlsruher Schriften zur Anthropomatik
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    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.

    Umfang: XIX, 210 S.

    Preis: €45.00 | £41.00 | $79.00

    Fächer:

    Informatik und Mathematik 

    Schlagwörter:

    Unsicherheit Quantifizierung generalized polynomial chaos verteilt-parametrische Systeme Uncertainty Quantification Distributed Parameter Systems Sensitivity Analysis Parameter estimation

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    Empfohlene Zitierweise
    Janya-anurak, C. 2017. Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000066940
    Janya-anurak, C., 2017. Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000066940
    Janya-anurak, C. Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based on Generalized Polynomial Chaos. KIT Scientific Publishing, 2017. DOI: https://doi.org/10.5445/KSP/1000066940
    Janya-anurak, C. (2017). Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000066940
    Janya-anurak, Chettapong. 2017. Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems Using Bayesian Uncertainty Quantification Based on Generalized Polynomial Chaos. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000066940



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    Weitere Informationen

    Veröffentlicht am 4. April 2017

    Sprache

    Englisch

    Seitenanzahl:

    248

    ISBN
    Paperback 978-3-7315-0642-3

    DOI
    https://doi.org/10.5445/KSP/1000066940