A new surrogate modeling technique combining Kriging and polynomial chaos expansions - application to uncertainty analysis in computational dosimetry
type: Item
instance of: scholarly article
title: A new surrogate modeling technique combining Kriging and polynomial chaos expansions - application to uncertainty analysis in computational dosimetry
zbMATH Open document ID: 1351.94003
author: Pierric Kersaudy
author: Bruno Sudret
author: Nadège Varsier
author: Odile Picon
author: Joe Wiart
published in: Journal of Computational Physics
publication date: 2016-12-20T00:00:00Z
Mathematics Subject Classification ID: 94A05
Mathematics Subject Classification ID: 65C60
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 6666640
zbMATH Keywords: polynomial chaos expansions
zbMATH Keywords: Kriging
zbMATH Keywords: least-angle regression
zbMATH Keywords: dosimetry
zbMATH Keywords: specific absorption rate
describes a project that uses: Matlab
describes a project that uses: EGO
describes a project that uses: AK-MCS
describes a project that uses: DACE
MaRDI profile type: Publication
full work available at URL: j.jcp.2015.01.034
OpenAlex ID: W1984584655
cites work: Q4232766
cites work: Adaptive sparse polynomial chaos expansion based on least angle regression
cites work: Q3394879
cites work: The design and analysis of computer experiments.
cites work: The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
cites work: Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure
cites work: A stochastic projection method for fluid flow. II: Random process
cites work: Stochastic finite element: a non intrusive approach by regression
cites work: Sparse polynomial chaos expansions and adaptive stochastic finite elements using a regression approach
cites work: Least angle regression. (With discussion)
cites work: A non-adapted sparse approximation of PDEs with stochastic inputs
cites work: A weighted \(\ell_1\)-minimization approach for sparse polynomial chaos expansions
cites work: Design and analysis of computer experiments. With comments and a rejoinder by the authors
cites work: Sequential design of computer experiments for the estimation of a probability of failure
cites work: Efficient global optimization of expensive black-box functions
cites work: A perfectly matched layer for the absorption of electromagnetic waves
cites work: An efficient methodology for modeling complex computer codes with Gaussian processes
cites work: Q2970771
cites work: Estimating Percentiles of Uncertain Computer Code Outputs
cites work: Q3331506
cites work: Cross validation and maximum likelihood estimations of hyper-parameters of Gaussian processes with model misspecification
cites work: Optimal Latin-hypercube designs for computer experiments
cites work: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
cites work: Q4514474
cites work: Bayesian Design and Analysis of Computer Experiments: Use of Derivatives in Surface Prediction
DOI: 10.1016/J.JCP.2015.01.034
description: scientific article; zbMATH DE number 6666640