A Machine Learning Based Hybrid Multi-Fidelity Multi-Level Monte Carlo Method for Uncertainty Quantification

A Machine Learning Based Hybrid Multi-Fidelity Multi-Level Monte Carlo Method for Uncertainty Quantification

This paper focuses on reducing the computational cost of the Monte Carlo method for uncertainty propagation. Recently, Multi-Fidelity Monte Carlo (MFMC) method (Ng, 2013; Peherstorfer et al., 2016) and Multi-Level Monte Carlo (MLMC) method (Müller et al., 2013; Giles, 2015) were introduced to reduce...

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Bibliographic Details
Main Authors: Nagoor Kani Jabarullah Khan, Ahmed H. Elsheikh
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-08-01
Series:Frontiers in Environmental Science
Subjects:
uncertainty quantification
POD
multi-fidelity Monte Carlo method
multi-level Monte Carlo method
machine learning
Online Access:https://www.frontiersin.org/article/10.3389/fenvs.2019.00105/full

Internet

https://www.frontiersin.org/article/10.3389/fenvs.2019.00105/full

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