A novel adaptive importance sampling algorithm based on Markov chain and low-discrepancy sequence

A novel adaptive importance sampling method is proposed to estimate the structural failure probability. It properly utilizes Markov chain algorithm to form an adaptive importance sampling procedure. The main concept is suggesting the proposal distributions of Markov chain as the importance sampling...

Full description

Saved in:

Bibliographic Details
Published in:	Aerospace science and technology Vol. 29; no. 1; pp. 253 - 261
Main Authors:	Yuan, Xiukai, Lu, Zhenzhou, Zhou, Changcong, Yue, Zhufeng
Format:	Journal Article
Language:	English
Published:	Issy-les-Moulineaux Elsevier Masson SAS 01.08.2013 Elsevier
Subjects:	Adaptive algorithms Algorithms Density Estimates Exact sciences and technology Failure Importance sampling Low-discrepancy sequence Markov chain Markov chains Markov processes Mathematical methods in physics Monte Carlo simulation Physics Probability theory, stochastic processes, and statistics Reliability Structural failure Markov chain Low-discrepancy sequence Reliability Monte Carlo simulation Importance sampling Markov process Monte Carlo methods Algorithms Digital simulation Modelling Adaptive method
ISSN:	1270-9638, 1626-3219
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!