.png){kind=icon}
Return
Probability density evolution method for structural reliability analysis: A parallel Bayesian active learning perspective
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compstruc.2025.107936.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Probability density evolution method is cast from Bayesian active learning perspective. • Bayesian inference of failure probability is conducted based on the Kriging prior. • A multi-point learning function is defined to reduce the uncertainty of failure probability. • Advantage of the goal-consistent batch enrichment strategy over others is clarified.
Keywords:
Probability density evolution method
Bayesian inference
Kriging prior
Failure probability
Multi-point learning function
Journal
C
IF:
4.8
Papers:
6.2K
Citations:
1.7W
Organization
View more organizations
Cited Papers
ShareSaveShareSaveActive learning and active subspace enhancement for PDEM-based high-dimensional reliability analysis.png)
STRUCTURAL SAFETY
STRUCTURAL SAFETYIF6.3
PREAI
ShareSaveShareSaveShareSaveShareSaveShareSaveShareSaveActive learning for structural reliability: Survey, general framework and benchmarkSTRUCTURAL SAFETY
OAAI
STRUCTURAL SAFETYIF6.3
OAAIShareSave View more