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Partial least squares-based polynomial chaos Kriging for high-dimensional reliability analysis
16 references·10 citing·44 second hop
Partial least squares-based polynomial chaos Kriging for high-dimensional reliability analysis (2023)Partial least squares-based polynomial ch…Support vector machine in structural reliability analysis: A review (2023)Support vector machine in str…Active learning for structural reliability: Survey, general framework and benchmark (2022)Active learning for structura…Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark (2021)Sparse Polynomial Chaos Expan…Machine learning-based methods in structural reliability analysis: A review (2021)Machine learning-based method…Adaptive approaches in metamodel-based reliability analysis: A review (2020)Adaptive approaches in metamo…Rare Event Estimation Using Polynomial-Chaos Kriging (2016)Rare Event Estimation Using P…A GF-discrepancy for point selection in stochastic seismic response analysis of structures with uncertain parameters (2015)A GF-discrepancy for point se…UQLab: A Framework for Uncertainty Quantification in Matlab 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(2025)Reliability analysis of struc…Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification (2025)Dimensionality reduction can …Combined dimensionality reduction based adaptive polynomial chaos expansion for high-dimensional reliability analysis (2025)Combined dimensionality reduc…An active learning method combining MRBF model and dimension-reduction importance sampling for reliability analysis with high dimensionality and very small failure probability (2025)An active learning method com…Active learning for high-dimensional reliability using matrix-operation anisotropic RBF model embedded with Multiscale Graph Correlation (2025)Active learning for high-dime…Structural reliability analysis based on probability density evolution method and stepwise truncated variance reduction (2024)Structural reliability analys…Incremental learning of parameter spaces in machine-learning based reliability analysis (2024)Incremental learning of param…AK–TSAGL: A two-stage hybrid algorithm combining global exploration and local exploitation based on active learning for structural reliability analysis (2024)AK–TSAGL: A two-stage hybrid …A novel active learning method based on matrix-operation RBF model for high-dimensional reliability analysis (2024)A novel active learning metho…Look-ahead active learning reliability analysis based on stepwise margin reduction (2023)Look-ahead active learning re…Simulation and the Monte Carlo Method (1981)The stochastic finite element method: Past, present and future (2008)A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)The generalization of Latin hypercube sampling (2015)Simulation and the Monte Carlo Method (2016)Stochastic Finite Elements: A Spectral Approach (1991)Structural Reliability Methods (1996)Kriging metamodeling in simulation: A review (2007)Metamodel-based importance sampling for structural 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(2010)Global sensitivity analysis using polynomial chaos expansions (2007)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis (2018)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses (2022)Monte Carlo solution of structural dynamics (1972)Stochastic Dynamics of Structures (2009)Direct probability integral method for stochastic response analysis of static and dynamic structural systems (2019)A unified analysis framework of static and dynamic structural reliabilities based on direct probability integral method (2021)System reliability analyses of static and dynamic structures via direct probability integral method (2021)Application of kriging method to structural reliability problems (2004)Structural reliability analysis based on improved wolf pack algorithm AK-SS (2023)Adaptive directed support vector machine method for the reliability evaluation of aeroengine structure (2024)Theory and application of possibility and evidence in reliability analysis and design optimization (2025)Narrow Reliability Bounds for Structural Systems (1979)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design (2004)
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References

  • 1974Exact and Invariant Second-Moment Code Format3,138 cited
  • 2001Estimation of small failure probabilities in high dimensions by subset simulation2,419 cited
  • 2011AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation2,048 cited
  • 2008Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions1,141 cited
  • 2014UQLab: A Framework for Uncertainty Quantification in Matlab1,018 cited
  • 2002On Latin hypercube sampling for structural reliability analysis798 cited
  • 1993Optimal Discretization of Random Fields728 cited
  • 2023Support vector machine in structural reliability analysis: A review507 cited
  • 2006The equivalent extreme-value event and evaluation of the structural system reliability447 cited
  • 2015A GF-discrepancy for point selection in stochastic seismic response analysis of structures with uncertain parameters410 cited
  • 2021Machine learning-based methods in structural reliability analysis: A review370 cited
  • 2008Calculations of Sobol indices for the Gaussian process metamodel331 cited
  • 2022Active learning for structural reliability: Survey, general framework and benchmark282 cited
  • 2020Adaptive approaches in metamodel-based reliability analysis: A review280 cited

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  • 2016Rare Event Estimation Using Polynomial-Chaos Kriging279 cited
  • 2021Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark275 cited
  • Cited by

    • 2024A novel active learning method based on matrix-operation RBF model for high-dimensional reliability analysis25 cited
    • 2023Look-ahead active learning reliability analysis based on stepwise margin reduction23 cited
    • 2025An active learning method combining MRBF model and dimension-reduction importance sampling for reliability analysis with high dimensionality and very small failure probability22 cited
    • 2024Incremental learning of parameter spaces in machine-learning based reliability analysis16 cited
    • 2025Combined dimensionality reduction based adaptive polynomial chaos expansion for high-dimensional reliability analysis15 cited
    • 2025Reliability analysis of structures by multiple sparse polynomial chaos expansion based adaptive metamodel15 cited
    • 2024AK–TSAGL: A two-stage hybrid algorithm combining global exploration and local exploitation based on active learning for structural reliability analysis14 cited
    • 2025Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification13 cited
    • 2024Structural reliability analysis based on probability density evolution method and stepwise truncated variance reduction11 cited
    • 2025Active learning for high-dimensional reliability using matrix-operation anisotropic RBF model embedded with Multiscale Graph Correlation8 cited