Efficient computing technique for reliability analysis of high-dimensional and low-failure probability problems using active learning method

In spite of recent advancements in reliability analysis, high-dimensional and low-failure probability problems remain challenging because many samples and function calls are required for an accurate result. Function calls lead to a sharp increase in computational cost in terms of time. For this reas...

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Veröffentlicht in:	Probabilistic engineering mechanics Jg. 77; S. 103662
Hauptverfasser:	Rajak, Pijus, Roy, Pronab
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2024
Schlagworte:	Active learning algorithm Kriging metamodel Sample selection strategy Space-filling design Stopping criterion Unsupervised clustering algorithm Active learning algorithm Stopping criterion Unsupervised clustering algorithm Space-filling design Sample selection strategy Kriging metamodel
ISSN:	0266-8920
Online-Zugang:	Volltext
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