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Rare-Event Simulation

Beck, James L. and Zuev, Konstantin M. (2017) Rare-Event Simulation. In: Handbook of Uncertainty Quantification. Springer , Cham, Switzerland, pp. 1075-1100. ISBN 978-3-319-12384-4. http://resolver.caltech.edu/CaltechAUTHORS:20170713-135954829

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Abstract

Rare events are events that are expected to occur infrequently or, more technically, those that have low probabilities (say, order of 10−3 or less) of occurring according to a probability model. In the context of uncertainty quantification, the rare events often correspond to failure of systems designed for high reliability, meaning that the system performance fails to meet some design or operation specifications. As reviewed in this section, computation of such rare-event probabilities is challenging. Analytical solutions are usually not available for nontrivial problems, and standard Monte Carlo simulation is computationally inefficient. Therefore, much research effort has focused on developing advanced stochastic simulation methods that are more efficient. In this section, we address the problem of estimating rare-event probabilities by Monte Carlo simulation, importance sampling, and subset simulation for highly reliable dynamic systems.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://dx.doi.org/10.1007/978-3-319-12385-1_24DOIArticle
https://link.springer.com/referenceworkentry/10.1007%2F978-3-319-12385-1_24PublisherArticle
Additional Information:© 2017 Springer International Publishing Switzerland.
Subject Keywords:Rare-event simulation; Dynamic system reliability; Monte carlo simulation; Subset simulation; Importance sampling; Splitting
Record Number:CaltechAUTHORS:20170713-135954829
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170713-135954829
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79094
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:13 Jul 2017 21:46
Last Modified:13 Jul 2017 21:46

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