Kriging-based adaptive Importance Sampling algorithms for rare event estimation

Very efficient sampling algorithms have been proposed to estimate rare event probabilities, such as Importance Sampling or Importance Splitting. Even if the number of samples required to apply these techniques is relatively low compared to Monte-Carlo simulations of same efficiency, it is often diff...

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Vydané v:	Structural safety Ročník 44; s. 1 - 10
Hlavní autori:	Balesdent, Mathieu, Morio, Jérôme, Marzat, Julien
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier Ltd 01.09.2013 Elsevier
Predmet:	Algorithms Applied sciences Computer simulation Estimates Exact sciences and technology Ground, air and sea transportation, marine construction Importance Sampling Input–output function Kriging Marine construction Rare event estimation Samples Sampling Statistical analysis Statistical methods Surrogate model Surrogate model Importance Sampling Input–output function Kriging Rare event estimation Estimation Aeronautics Spacecraft Probability Input-output function Rare event Modeling Adaptive method Statistics Case study Input output analysis Launching Safety Sampling
ISSN:	0167-4730, 1879-3355
On-line prístup:	Získať plný text
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