An active learning kriging model for hybrid reliability analysis with both random and interval variables-Reference-Cited by-同舟云学术

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An active learning kriging model for hybrid reliability analysis with both random and interval variables

Published:2014-11-19 Issue:5 Volume:51 Page:1003-1016
ISSN:1615-147X
Container-title:Structural and Multidisciplinary Optimization
language:en
Short-container-title:Struct Multidisc Optim

Author:

Yang Xufeng,Liu Yongshou,Gao Yi,Zhang Yishang,Gao Zongzhan

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,Computer Graphics and Computer-Aided Design,Computer Science Applications,Control and Systems Engineering,Software

Link

http://link.springer.com/content/pdf/10.1007/s00158-014-1189-5.pdf

Reference36 articles.

1. Au S, Papadimitriou C, Beck J (1999) Reliability of uncertain dynamical systems with multiple design points. Struct Saf 21:113–133

2. Balesdent M, Morio J, Marzat J (2013) Kriging-based adaptive importance sampling algorithms for rare event estimation. Struct Saf 44:1–10

3. Bect J, Ginsbourger D, Li L et al (2012) Sequential design of computer experiments for the estimation of a probability of failure. Stat Comput 22:773–793

4. Bichon B, Eldred M, Swiler L et al (2008) Efficient global reliability analysis for nonlinear implicit performance functions. AIAA J 46:2459–2468

5. Bichon B, McFarland J, Mahadevan S (2011) Efficient surrogate models for reliability analysis of systems with multiple failure modes. Reliab Eng Syst Saf 96:1386–1395

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