Novel reliability evaluation method combining active learning kriging and adaptive weighted importance sampling-Reference-Cited by-同舟云学术

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Novel reliability evaluation method combining active learning kriging and adaptive weighted importance sampling

Published:2022-08-23 Issue:9 Volume:65 Page:
ISSN:1615-147X
Container-title:Structural and Multidisciplinary Optimization
language:en
Short-container-title:Struct Multidisc Optim

Author:

Tang Chenghu,Zhang Feng^ORCID,Zhang Jianhua,Lv Yi,Wang Gangfeng

Funder

Key Laboratory of Expressway Construction Machinery of Shaanxi Province

Foundation Research Funds of Xi’an Aeronautical Institute

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

https://link.springer.com/content/pdf/10.1007/s00158-022-03346-2.pdf

Reference47 articles.

1. Abdollahi A, Azhdary Moghaddam M, Hashemi Monfared SA, Rashki M, Li Y (2021) Subset simulation method including fitness-based seed selection for reliability analysis. Eng Comput 37:2689–2705

2. Au S, Beck JL (1999) A new adaptive importance sampling scheme for reliability calculations. Struct Saf 21:135–158

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

4. Bichon BJ, Eldred MS, Swiler LP, Mahadevan S, McFarland JM (2008) Efficient global reliability analysis for nonlinear implicit performance functions. AIAA J 46:2459–2468

5. Cadini F, Santos F, Zio E (2014) An improved adaptive kriging-based importance technique for sampling multiple failure regions of low probability. Reliab Eng Syst Saf 131:109–117

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