Structural reliability analysis based on ensemble learning of surrogate modelsKai Cheng, Zhenzhou Lü2019-11-19articleStructural Safety146 citationsclosedNo readable copy stored yet — this record is metadata only.Probabilistic and Robust Engineering DesignGeotechnical Engineering and AnalysisAdvanced Multi-Objective Optimization AlgorithmsAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 146 citations exist upstream.References2007Global sensitivity analysis using polynomial chaos expansions2001Estimation of small failure probabilities in high dimensions by subset simulation2011AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation2010Adaptive sparse polynomial chaos expansion based on least angle regression2008Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions2009An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis2008Polynomial chaos expansion for sensitivity analysis2012A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical modelsCited by2020Adaptive Bayesian support vector regression model for structural reliability analysis2021AKSE: A novel adaptive Kriging method combining sampling region scheme and error-based stopping criterion for structural reliability analysis2022Ensemble of surrogates combining Kriging and Artificial Neural Networks for reliability analysis with local goodness measurement2020An active-learning method based on multi-fidelity Kriging model for structural reliability analysis2024A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications2021Efficient structural reliability analysis based on adaptive Bayesian support vector regression2022A novel surrogate-model based active learning method for structural reliability analysis2020Active sparse polynomial chaos expansion for system reliability analysis