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Implementation of machine learning techniques into the Subset Simulation method
16 references·11 citing·30 second hop
Implementation of machine learning techniques into the Subset Simulation method (2019)Implementation of machine learning techni…Structural Reliability Analysis and Prediction (2017)Structural Reliability Analys…Simulation and the Monte Carlo Method (2016)Simulation and the Monte Carl…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 combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)A combined Importance Samplin…Assessing small failure probabilities by combined subset simulation and Support Vector Machines (2011)Assessing small failure proba…AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)AK-MCS: An active learning re…Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions (2008)Efficient Global Reliability …Application of kriging method to structural reliability problems (2004)Application of kriging method…Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Latin hypercube sampling and …Important sampling in high dimensions (2002)Important sampling in high di…Estimation of small failure probabilities in high dimensions by subset simulation (2001)Estimation of small failure p…Structural Reliability Methods (1996)Structural Reliability MethodsImportance sampling in structural systems (1989)Importance sampling in struct…Large Sample Properties of Simulations Using Latin Hypercube Sampling (1987)Large Sample Properties of Si…Simulation and the Monte Carlo Method (1981)Simulation and the Monte Carl…The return of the design points (2024)The return of the design poin…A novel decoupled approach combining invertible cross-entropy method with Gaussian process modeling for reliability-based design and topology optimization (2024)A novel decoupled approach co…RBIK-SS: A parallel adaptive structural reliability analysis method for rare failure events (2023)RBIK-SS: A parallel adaptive …An efficient sequential anisotropic RBF reliability analysis method with fast cross-validation and parallelizability (2023)An efficient sequential aniso…Efficient subset simulation with active learning Kriging model for low failure probability prediction (2022)Efficient subset simulation w…Combined relevance vector machine technique and subset simulation importance sampling for structural reliability (2022)Combined relevance vector mac…Bayesian inversion using adaptive Polynomial Chaos Kriging within Subset Simulation (2022)Bayesian inversion using adap…Active learning with multifidelity modeling for efficient rare event simulation (2022)Active learning with multifid…SORM, Design Points, Subset Simulation, and Markov Chain Monte Carlo (2021)SORM, Design Points, Subset S…An Active Kriging-Based Learning Method for Hybrid Reliability Analysis (2021)An Active Kriging-Based Learn…Reliability assessment with density scanned adaptive Kriging (2020)Reliability assessment with d…Stochastic Finite Elements: A Spectral Approach (1991)Kriging metamodeling in simulation: A review (2007)Metamodel-based importance sampling for structural reliability analysis (2013)LIF: A new Kriging based learning function and its application to structural reliability analysis (2016)On the Experimental Attainment of Optimum Conditions (1951)A fast and efficient response surface approach for structural reliability problems (1990)On the Experimental Attainment of Optimum Conditions (1992)Support vector machine in structural reliability analysis: A review (2023)Structural reliability under combined random load sequences (1978)Designs for Computer Experiments (1989)Probability, reliability and statistical methods in engineering design (1999)DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. 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References

  • 2017Structural Reliability Analysis and Prediction3,780 cited
  • 2016Simulation and the Monte Carlo Method3,356 cited
  • 2003Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems2,707 cited
  • 1987Large Sample Properties of Simulations Using Latin Hypercube Sampling2,483 cited
  • 2001Estimation of small failure probabilities in high dimensions by subset simulation2,419 cited
  • 1981Simulation and the Monte Carlo Method2,402 cited
  • 1996Structural Reliability Methods2,192 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
  • 2004Application of kriging method to structural reliability problems709 cited
  • 2012A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models692 cited
  • 1989Importance sampling in structural systems604 cited
  • 2011Assessing small failure probabilities by combined subset simulation and Support Vector Machines419 cited
  • 2015MCMC algorithms for Subset Simulation413 cited
  • 2016Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation

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412 cited
  • 2002Important sampling in high dimensions375 cited
  • Cited by

    • 2020Reliability assessment with density scanned adaptive Kriging43 cited
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    • 2022Combined relevance vector machine technique and subset simulation importance sampling for structural reliability38 cited
    • 2023An efficient sequential anisotropic RBF reliability analysis method with fast cross-validation and parallelizability36 cited
    • 2023RBIK-SS: A parallel adaptive structural reliability analysis method for rare failure events35 cited
    • 2022Efficient subset simulation with active learning Kriging model for low failure probability prediction30 cited
    • 2024A novel decoupled approach combining invertible cross-entropy method with Gaussian process modeling for reliability-based design and topology optimization24 cited
    • 2024The return of the design points21 cited
    • 2021SORM, Design Points, Subset Simulation, and Markov Chain Monte Carlo20 cited
    • 2021An Active Kriging-Based Learning Method for Hybrid Reliability Analysis20 cited
    • 2022Bayesian inversion using adaptive Polynomial Chaos Kriging within Subset Simulation14 cited