Quasi-Monte Carlo based uncertainty analysis: Sampling efficiency and error estimation in engineering applications

November 2019 - Posted: 11/8/2019


In probabilistic assessment via Monte Carlo sampling efficiency is of high importance. It is shown that Quasi-Monte Carlo mostly performs better than standard Monte Carlo. Depending on the smoothness of the function and the number of dominant parameters. Randomization techniques on Quasi-Monte Carlo allows assessing sampling accuracy.In probabilistic assessment via Monte Carlo sampling efficiency is of high importance. It is shown that Quasi-Monte Carlo mostly performs better than standard Monte Carlo. Depending on the smoothness of the function and the number of dominant parameters. Randomization techniques on Quasi-Monte Carlo allows assessing sampling accuracy.



 



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By: Tianfeng Hou, Dirk Nuyens, Staf Roels, Hans Janssen
Publisher: Reliability Engineering & System Safety, Volume 191