A new active-learning function for adaptive Polynomial-Chaos Kriging probability density evolution method
出版年份 2022 全文链接
标题
A new active-learning function for adaptive Polynomial-Chaos Kriging probability density evolution method
作者
关键词
Active-learning function, Information entropy, Probability density evolution method, Region of interest, Probability of failure
出版物
APPLIED MATHEMATICAL MODELLING
Volume 106, Issue -, Pages 86-99
出版商
Elsevier BV
发表日期
2022-02-09
DOI
10.1016/j.apm.2022.01.030
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Active learning for structural reliability: Survey, general framework and benchmark
- (2022) Maliki Moustapha et al. STRUCTURAL SAFETY
- Reliability analysis using adaptive Polynomial-Chaos Kriging and probability density evolution method
- (2021) Tong Zhou et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- A combined radial basis function and adaptive sequential sampling method for structural reliability analysis
- (2020) Linxiong Hong et al. APPLIED MATHEMATICAL MODELLING
- Adaptive approaches in metamodel-based reliability analysis: A review
- (2020) Rui Teixeira et al. STRUCTURAL SAFETY
- An efficient reliability method combining adaptive global metamodel and probability density evolution method
- (2019) Tong Zhou et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Generalized F‐discrepancy‐based point selection strategy for dependent random variables in uncertainty quantification of nonlinear structures
- (2019) Junyi Yang et al. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
- A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis
- (2018) Ning-Cong Xiao et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis
- (2018) Stefano Marelli et al. STRUCTURAL SAFETY
- High dimensional structural reliability with dimension reduction
- (2017) Zhongming Jiang et al. STRUCTURAL SAFETY
- Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions
- (2016) Katerina Konakli et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Rare-event probability estimation with adaptive support vector regression surrogates
- (2016) J.-M. Bourinet RELIABILITY ENGINEERING & SYSTEM SAFETY
- A GF-discrepancy for point selection in stochastic seismic response analysis of structures with uncertain parameters
- (2016) Jianbing Chen et al. STRUCTURAL SAFETY
- Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation
- (2016) Xiaoxu Huang et al. STRUCTURAL SAFETY
- An efficient reliability method combining adaptive importance sampling and Kriging metamodel
- (2015) Hailong Zhao et al. APPLIED MATHEMATICAL MODELLING
- A new learning function for Kriging and its applications to solve reliability problems in engineering
- (2015) Zhaoyan Lv et al. COMPUTERS & MATHEMATICS WITH APPLICATIONS
- POLYNOMIAL-CHAOS-BASED KRIGING
- (2015) Roland Schobi et al. International Journal for Uncertainty Quantification
- Advances of the probability density evolution method for nonlinear stochastic systems
- (2011) Jie Li et al. PROBABILISTIC ENGINEERING MECHANICS
- AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation
- (2011) B. Echard et al. STRUCTURAL SAFETY
- Adaptive sparse polynomial chaos expansion based on least angle regression
- (2010) Géraud Blatman et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions
- (2008) B. J. Bichon et al. AIAA JOURNAL
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started