A combined Importance Sampling and active learning Kriging reliability method for small failure probability with random and correlated interval variables
Abstract
The existing hybrid reliability analysis (HRA) method (Yang et al., 2015; Zhang et al., 2015; Yang et al., 2015) is found not suitable for estimating small failure probabilities. Meanwhile, the previous ALK-HRA algorithm (ALK-HRA: an active learning HRA method combining Kriging and Monte Carlo simulation) reduces its numerical efficiency when number of uncertain variables increases. Furthermore, the ALK-HRA approach with both random and...
Paper Details
Title
A combined Importance Sampling and active learning Kriging reliability method for small failure probability with random and correlated interval variables
Published Date
Jan 1, 2020
Journal
Volume
82
Pages
101875 - 101875
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History