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Uncertainty quantificationan acceler...
~
Soize, Christian.
Uncertainty quantificationan accelerated course with advanced applications in computational engineering /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Uncertainty quantificationby Christian Soize.
Reminder of title:
an accelerated course with advanced applications in computational engineering /
Author:
Soize, Christian.
Published:
Cham :Springer International Publishing :2017.
Description:
xxii, 329 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer eBooks
Subject:
UncertaintyMathematical models.
Online resource:
http://dx.doi.org/10.1007/978-3-319-54339-0
ISBN:
9783319543390$q(electronic bk.)
Uncertainty quantificationan accelerated course with advanced applications in computational engineering /
Soize, Christian.
Uncertainty quantification
an accelerated course with advanced applications in computational engineering /[electronic resource] :by Christian Soize. - Cham :Springer International Publishing :2017. - xxii, 329 p. :ill. (some col.), digital ;24 cm. - Interdisciplinary applied mathematics,v.470939-6047 ;. - Interdisciplinary applied mathematics ;v. 21..
Fundamental Notions in Stochastic Modeling of Uncertainties and their Propagation in Computational Models -- Elements of Probability Theory -- Markov Process and Stochastic Differential Equation -- MCMC Methods for Generating Realizations and for Estimating the Mathematical Expectation of Nonlinear Mappings of Random Vectors -- Fundamental Probabilistic Tools for Stochastic Modeling of Uncertainties -- Brief Overview of Stochastic Solvers for the Propagation of Uncertainties -- Fundamental Tools for Statistical Inverse Problems -- Uncertainty Quantification in Computational Structural Dynamics and Vibroacoustics -- Robust Analysis with Respect to the Uncertainties for Analysis, Updating, Optimization, and Design -- Random Fields and Uncertainty Quantification in Solid Mechanics of Continuum Media.
ISBN: 9783319543390$q(electronic bk.)
Standard No.: 10.1007/978-3-319-54339-0doiSubjects--Topical Terms:
263216
Uncertainty
--Mathematical models.
LC Class. No.: QA273
Dewey Class. No.: 003.54
Uncertainty quantificationan accelerated course with advanced applications in computational engineering /
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Fundamental Notions in Stochastic Modeling of Uncertainties and their Propagation in Computational Models -- Elements of Probability Theory -- Markov Process and Stochastic Differential Equation -- MCMC Methods for Generating Realizations and for Estimating the Mathematical Expectation of Nonlinear Mappings of Random Vectors -- Fundamental Probabilistic Tools for Stochastic Modeling of Uncertainties -- Brief Overview of Stochastic Solvers for the Propagation of Uncertainties -- Fundamental Tools for Statistical Inverse Problems -- Uncertainty Quantification in Computational Structural Dynamics and Vibroacoustics -- Robust Analysis with Respect to the Uncertainties for Analysis, Updating, Optimization, and Design -- Random Fields and Uncertainty Quantification in Solid Mechanics of Continuum Media.
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EB QA273 S683 2017
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http://dx.doi.org/10.1007/978-3-319-54339-0
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