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RBIK-SS: A parallel adaptive structural reliability analysis method for rare failure events
16 references·13 citing·26 second hop
RBIK-SS: A parallel adaptive structural reliability analysis method for rare failure events (2023)RBIK-SS: A parallel adaptive structural r…A review and assessment of importance sampling methods for reliability analysis (2022)A review and assessment of im…REIF: A novel active-learning function toward adaptive Kriging surrogate models for structural reliability analysis (2019)REIF: A novel active-learning…AK-MCSi: A Kriging-based method to deal with small failure probabilities and time-consuming models (2018)AK-MCSi: A Kriging-based meth…An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation (2017)An efficient reliability meth…Sequential importance sampling for structural reliability analysis (2016)Sequential importance samplin…Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation (2016)Assessing small failure proba…MCMC algorithms for Subset Simulation (2015)MCMC algorithms for Subset Si…A new learning function for Kriging and its applications to solve reliability problems in engineering (2015)A new learning function for K…An improved adaptive kriging-based importance technique for sampling multiple failure regions of low probability (2014)An improved adaptive kriging-…Metamodel-based importance sampling for structural reliability analysis (2013)Metamodel-based importance sa…Accelerated subset simulation with neural networks for reliability analysis (2012)Accelerated subset simulation…A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)A combined Importance Samplin…AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)AK-MCS: An active learning re…Comparison of response surface and neural network with other methods for structural reliability analysis (2003)Comparison of response surfac…Estimation of small failure probabilities in high dimensions by subset simulation (2001)Estimation of small failure p…A new adaptive importance sampling scheme for reliability calculations (1999)A new adaptive importance sam…Sequential and adaptive probabilistic integration for structural reliability analysis (2025)Sequential and adaptive proba…Parallel active learning XGBoost for structural reliability analysis with application to an onshore wind turbine tower (2025)Parallel active learning XGBo…PAKP: Parallelized Adaptive Kriging method with Partial least squares for high-dimensional reliability analysis (2025)PAKP: Parallelized Adaptive K…AEK-MFIS: An adaptive ensemble of Kriging models based on multi-fidelity simulations and importance sampling for small failure probabilities (2025)AEK-MFIS: An adaptive ensembl…A theoretically-consistent parallel enrichment strategy for Bayesian active learning reliability analysis (2025)A theoretically-consistent pa…A novel active learning reliability analysis method based on ensemble of Kriging models and importance sampling for small failure probabilities (2025)A novel active learning relia…Parallel active learning reliability analysis: A multi-point look-ahead paradigm (2024)Parallel active learning reli…Multi-point Bayesian active learning reliability analysis (2024)Multi-point Bayesian active l…AK-Gibbs: An active learning Kriging model based on Gibbs importance sampling algorithm for small failure probabilities (2024)AK-Gibbs: An active learning …A physics-informed neural network enhanced importance sampling (PINN-IS) for data-free reliability analysis (2024)A physics-informed neural net…A novel active learning Kriging based on improved Metropolis-Hastings and importance sampling for small failure probabilities (2024)A novel active learning Krigi…A method of combined metamodel and subset simulation for reliability analysis of rare events (2024)A method of combined metamode…A new active learning method for system reliability analysis with multiple failure modes (2023)A new active learning method …Structural reliability under combined random load sequences (1978)Stochastic Finite Elements: A Spectral Approach (1991)Adaptive approaches in metamodel-based reliability analysis: A review (2020)Machine learning-based methods in structural reliability analysis: A review (2021)Active learning for structural reliability: Survey, general framework and benchmark (2022)Simulation and the Monte Carlo Method (1981)The stochastic finite element method: Past, present and future (2008)The generalization of Latin hypercube sampling (2015)Simulation and the Monte Carlo Method (2016)Optimization algorithms for structural reliability (1991)A critical appraisal of reliability estimation procedures for high dimensions (2004)Structural Reliability Methods (1996)Kriging metamodeling in simulation: A review (2007)LIF: A new Kriging based learning function and its application to structural reliability analysis (2016)Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Uniform Design: Theory and Application (2000)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Exact and Invariant Second-Moment Code Format (1974)The Design and Analysis of Computer Experiments (2003)Hybrid enhanced Monte Carlo simulation coupled with advanced machine learning approach for accurate and efficient structural reliability analysis (2021)Design and Analysis of Computer Experiments (1989)POLYNOMIAL-CHAOS-BASED KRIGING (2015)Simulation and the Monte Carlo Method (2007)Bayesian Updating with Structural Reliability Methods (2014)Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review (2023)
this work references cited by second hop

References

  • 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
  • 2012A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models692 cited
  • 1999A new adaptive importance sampling scheme for reliability calculations564 cited
  • 2013Metamodel-based importance sampling for structural reliability analysis535 cited
  • 2015MCMC algorithms for Subset Simulation413 cited
  • 2016Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation412 cited
  • 2015A new learning function for Kriging and its applications to solve reliability problems in engineering400 cited
  • 2019REIF: A novel active-learning function toward adaptive Kriging surrogate models for structural reliability analysis297 cited
  • 2017An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation290 cited
  • 2003Comparison of response surface and neural network with other methods for structural reliability analysis284 cited
  • 2014An improved adaptive kriging-based importance technique for sampling multiple failure regions of low probability278 cited
  • 2022A review and assessment of importance sampling methods for reliability analysis273 cited

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  • 2016Sequential importance sampling for structural reliability analysis267 cited
  • 2018AK-MCSi: A Kriging-based method to deal with small failure probabilities and time-consuming models218 cited
  • 2012Accelerated subset simulation with neural networks for reliability analysis213 cited
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    • 2025A theoretically-consistent parallel enrichment strategy for Bayesian active learning reliability analysis23 cited
    • 2024A physics-informed neural network enhanced importance sampling (PINN-IS) for data-free reliability analysis20 cited
    • 2024AK-Gibbs: An active learning Kriging model based on Gibbs importance sampling algorithm for small failure probabilities19 cited
    • 2025Sequential and adaptive probabilistic integration for structural reliability analysis17 cited
    • 2024Parallel active learning reliability analysis: A multi-point look-ahead paradigm15 cited
    • 2025AEK-MFIS: An adaptive ensemble of Kriging models based on multi-fidelity simulations and importance sampling for small failure probabilities14 cited
    • 2024A method of combined metamodel and subset simulation for reliability analysis of rare events13 cited
    • 2024A novel active learning Kriging based on improved Metropolis-Hastings and importance sampling for small failure probabilities13 cited
    • 2025PAKP: Parallelized Adaptive Kriging method with Partial least squares for high-dimensional reliability analysis11 cited
    • 2025Parallel active learning XGBoost for structural reliability analysis with application to an onshore wind turbine tower10 cited
    • 2025A novel active learning reliability analysis method based on ensemble of Kriging models and importance sampling for small failure probabilities9 cited