Results 191 to 200 of about 767,107 (236)
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SPE Journal, 2019
Bayesian inference provides a convenient framework for history matching and prediction. In this framework, prior knowledge, system nonlinearity, and measurement errors can be directly incorporated into the posterior distribution of the parameters.
Q. Liao +3 more
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Bayesian inference provides a convenient framework for history matching and prediction. In this framework, prior knowledge, system nonlinearity, and measurement errors can be directly incorporated into the posterior distribution of the parameters.
Q. Liao +3 more
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Stochastic Projection and Collocation
2018This chapter is concerned with expansions of functions of random variables in terms of common random variables. The chapter covers spectral expansions (polynomial chaos methods) and computational realizations of this using quadrature, collocation, and Galerkin projection. Sparse quadratures are also discussed to evaluate multiple dimensional integrals.
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Efficient Stochastic Optimization using Chaos Collocation Method with modeFRONTIER
SAE International Journal of Materials and Manufacturing, 2008<div class="htmlview paragraph">Robust Design Optimization (RDO) using traditional approaches such as Monte Carlo (MC) sampling requires tremendous computational expense. Performing a RDO for problems involving time consuming CAE analysis may not even be possible within time constraints.
PEDIRODA, VALENTINO +5 more
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AIP Conference Proceedings, 2012
In this paper, we investigate the model of three-dimensional (3D) stochastic multi-symplectic Hamiltonian Maxwell's equations, and consider the stochastic multi-symplectic numerical methods of solving such equations. In particular, multi-symplectic wavelet collocation method (MSWCM) is applied to such equations.
Jialin Hong, Lihai Ji
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In this paper, we investigate the model of three-dimensional (3D) stochastic multi-symplectic Hamiltonian Maxwell's equations, and consider the stochastic multi-symplectic numerical methods of solving such equations. In particular, multi-symplectic wavelet collocation method (MSWCM) is applied to such equations.
Jialin Hong, Lihai Ji
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An h-adaptive stochastic collocation method for stochastic EMC/EMI analysis
2010 IEEE Antennas and Propagation Society International Symposium, 2010The analysis of electromagnetic compatibility and interference (EMC/EMI) phenomena is often fraught by randomness in a system's excitation (e.g., the amplitude, phase, and location of internal noise sources) or configuration (e.g., the routing of cables, the placement of electronic systems, component specifications, etc.).
Abdulkadir C Yucel +2 more
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Multilevel Adaptive Stochastic Collocation with Dimensionality Reduction
2018We present a multilevel stochastic collocation (MLSC) with a dimensionality reduction approach to quantify the uncertainty in computationally intensive applications. Standard MLSC typically employs grids with predetermined resolutions. Even more, stochastic dimensionality reduction has not been considered in previous MLSC formulations.
Ionuţ-Gabriel Farcaş +4 more
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Collocation methods for nonlinear stochastic Volterra integral equations
Computational and Applied Mathematics, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiaoli Xu, Yu Xiao, Haiying Zhang
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Adjoint Error Estimation for Stochastic Collocation Methods
2014This paper deals with partial differential equations with random input data. An efficient way of solving such problems is adaptive stochastic collocation on sparse grids. For higher efficiency and a better understanding of the method, we derive adjoint error estimates for nonlinear stochastic solution functionals.
Bettina Schieche, Jens Lang
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Stochastic collocation enhanced line sampling method for reliability analysis
Reliability Engineering & System Safety, 2023Ning Wei, Zhenzhou Lu, Yingshi Hu
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Journal of Mathematical Analysis and Applications, 2023
Fenglin Huang +3 more
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Fenglin Huang +3 more
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