Results 81 to 90 of about 12,137 (169)

On fractional moment estimation from polynomial chaos expansion

Reliability Engineering & System Safety
Fractional statistical moments are utilized for various tasks of uncertainty quantification, including the estimation of probability distributions. However, an estimation of fractional statistical moments of costly mathematical models by statistical sampling is challenging since it is typically not possible to create a large experimental design due to ...
Lukáš Novák, Marcos Valdebenito, Matthias Faes   +2 more
openaire   +2 more sources

Sparse polynomial chaos expansion for universal stochastic kriging

Journal of Computational and Applied Mathematics
Surrogate modelling techniques have opened up new possibilities to overcome the limitations of computationally intensive numerical models in various areas of engineering and science. However, while fundamental in many engineering applications and decision-making, the incorporation of uncertainty quantification into meta-models remains a challenging ...
J.C. García-Merino, C. Calvo-Jurado, E. García-Macías   +2 more
openaire   +4 more sources

Polynomial Chaos Expansion Based Rauch–Tung–Striebel Smoothers

2024 27th International Conference on Information Fusion (FUSION)
Peer ...
Kumar Kundan, Särkkä Simo
openaire   +2 more sources

Combining Polynomial Chaos Expansions and Kriging

, 2014
Computer simulation has emerged as a key tool for designing and assessing engineeringsystems in the last two decades. Uncertainty quantification has becomepopular more recently as a way to model all the uncertainties affecting the systemand their impact onto its performance.In this respect meta-models (a.k.a.
Schöbi, R., Kersaudy, P., Sudret, B., Wiart, J.   +3 more
openaire   +1 more source

Global sensitivity of MEG source analysis to tissue conductivity uncertainties

NeuroImage
The influence of inter-individual variations of tissue conductivities on MEG source analysis is generally assumed to be small in comparison to EEG source analysis and the resulting effects on MEG source analysis have therefore been investigated much less.
Johannes Vorwerk, Malte B. Höltershinken, Carsten H. Wolters, Daniel Baumgarten   +3 more
doaj   +1 more source

Autocalibration of the E3SM Version 2 Atmosphere Model Using a PCA‐Based Surrogate for Spatial Fields

Journal of Advances in Modeling Earth Systems
Global Climate Model tuning (calibration) is a tedious and time‐consuming process, with high‐dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand‐picked values of tuning parameters.
Drew Yarger, Benjamin Moore Wagman, Kenny Chowdhary, Lyndsay Shand   +3 more
doaj   +1 more source

mumpce_py: A Python Implementation of the Method of Uncertainty Minimization Using Polynomial Chaos Expansions. [PDF]

J Res Natl Inst Stand Technol, 2017
Sheen DA.
europepmc   +1 more source

Free Choice in Quantum Theory: A p-adic View. [PDF]

Entropy (Basel), 2023
Anashin V.
europepmc   +1 more source

HPOSS: A hierarchical portfolio optimization stacking strategy to reduce the generalization error of ensembles of models. [PDF]

PLoS One, 2023
Ozelim LCSM, Ribeiro DB, Schiavon JA, Domingues VR, Queiroz PIB.   +4 more
europepmc   +1 more source

Improving the accuracy of retrieved cardiac electrical conductivities. [PDF]

ANZIAM j, 2022
Kamalakkanna A, Johnston PR, Johnston BM.   +2 more
europepmc   +1 more source