Data-Driven Method to Quantify Correlated Uncertainties

Data-Driven Method to Quantify Correlated Uncertainties

Polynomial chaos (PC) has been proven to be an efficient method for uncertainty quantification, but its applicability is limited by two strong assumptions: the mutual independence of random variables and the requirement of exact knowledge about the distribution of the random variables. We describe a...

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Bibliographic Details
Main Authors:	Jeahan Jung, Minseok Choi
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Series:	IEEE Access
Subjects:	Correlated random variables high dimension polynomial chaos expansion uncertainty quantification
Online Access:	https://ieeexplore.ieee.org/document/10129195/

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