Stochastic data assimilation of the random shallow water model loads with uncertain experimental measurements
type: Item
instance of: scholarly article
title: Stochastic data assimilation of the random shallow water model loads with uncertain experimental measurements
zbMATH Open document ID: 1398.76188
author: L. Mathelin
author: C. Desceliers
author: M. Yousuff Hussaini
published in: Computational Mechanics
publication date: 2011-07-01T00:00:00Z
full work available at URL: 2011 - Computational Mechanics - Mathelin - Desceliers - Hussaini .pdf
Mathematics Subject Classification ID: 76M35
Mathematics Subject Classification ID: 76B15
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 60H35
Mathematics Subject Classification ID: 60H15
Mathematics Subject Classification ID: 65Y05
Mathematics Subject Classification ID: 65C30
Mathematics Subject Classification ID: 74S05
zbMATH DE Number: 5916840
zbMATH Keywords: parametric estimation
zbMATH Keywords: stochastic inverse method
zbMATH Keywords: polynomial chaos
zbMATH Keywords: data assimilation
zbMATH Keywords: maximum likelihood
MaRDI profile type: Publication
OpenAlex ID: W2051508219
cites work: Parallel Lagrange--Newton--Krylov--Schur Methods for PDE-Constrained Optimization. Part I: The Krylov--Schur Solver
cites work: Maximum likelihood estimation of stochastic chaos representations from experimental data
cites work: Identification of chaos representations of elastic properties of random media using experimental vibration tests
cites work: An additive Schwarz preconditioner for the spectral element ocean model formulation of the shallow water equations
cites work: Maximum penalized likelihood estimation. Vol. 1: Density estimation
cites work: Polynomial Chaos in Stochastic Finite Elements
cites work: Q4232766
cites work: Some numerical experiments with variable-storage quasi-Newton algorithms
cites work: A staggered spectral element model with application to the oceanic shallow water equations
cites work: A multi-resolution, non-parametric, Bayesian framework for identification of spatially-varying model parameters
cites work: Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems
cites work: Stochastic spectral methods for efficient Bayesian solution of inverse problems
cites work: Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data
cites work: Computational Aspects for Constructing Realizations of Polynomial Chaos in High Dimension
cites work: Reduced chaos decomposition with random coefficients of vector-valued random variables and random fields
cites work: A Bayesian inference approach to the inverse heat conduction problem
cites work: Q5483525
cites work: A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach
DOI: 10.1007/S00466-010-0560-7
description: scientific article; zbMATH DE number 5916840