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An efficient method based on Bayes’ theorem to estimate the failure-probability-based sensitivity measure
16 references·8 citing·23 second hop
An efficient method based on Bayes’ theorem to estimate the failure-probability-based sensitivity measure (2018)An efficient method based on Bayes’ theor…Variable importance analysis: A comprehensive review (2015)Variable importance analysis:…Sensitivity analysis: A review of recent advances (2015)Sensitivity analysis: A revie…Risk assessment and risk management: Review of recent advances on their foundation (2015)Risk assessment and risk mana…Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Variance based sensitivity an…Subset simulation for structural reliability sensitivity analysis (2008)Subset simulation for structu…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Engineering computation under uncertainty – Capabilities of non-traditional models (2007)Engineering computation under…An effective screening design for sensitivity analysis of large models (2007)An effective screening design…A new uncertainty importance measure (2006)A new uncertainty importance …Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2005)Sensitivity Analysis in Pract…Reliability-based design sensitivity by efficient simulation (2005)Reliability-based design sens…Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2004)Sensitivity Analysis in Pract…Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…Sensitivity analysis: Could better methods be used? (1999)Sensitivity analysis: Could b…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…Factorial Sampling Plans for Preliminary Computational Experiments (1991)Factorial Sampling Plans for …A single-loop reliability sensitivity analysis strategy for time-dependent rare events with both random variables and stochastic processes (2024)A single-loop reliability sen…A novel single-loop estimation method for predictive failure probability-based global sensitivity analysis (2024)A novel single-loop estimatio…Time-variant reliability global sensitivity analysis with single-loop Kriging model combined with importance sampling (2023)Time-variant reliability glob…Reliability-based design optimization scheme of isolation capacity of nonlinear vibration isolators (2023)Reliability-based design opti…An improved adaptive Kriging model for importance sampling reliability and reliability global sensitivity analysis (2023)An improved adaptive Kriging …A novel Bayesian-inference-based method for global sensitivity analysis of system reliability with multiple failure modes (2023)A novel Bayesian-inference-ba…Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model (2022)Approach for the structural r…New Importance Measures Based on Failure Probability in Global Sensitivity Analysis of Reliability (2021)New Importance Measures Based…Statistics for Experimenters (1979)Design and Analysis of Computer Experiments (1989)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Handbook on Constructing Composite Indicators (2005)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)On The Quantitative Definition of Risk (1981)Perspectives in supply chain risk management (2006)The black swan: the impact of the highly improbable (2007)The future of risk assessment (2018)Understanding Compound, Interconnected, Interacting, and Cascading Risks: A Holistic Framework (2018)Flexibility and Resilience in Corporate Decision Making: A New Sustainability-Based Risk Management System in Uncertain Times (2021)Risk, Ambiguity, and the Savage Axioms (1961)The Price of Robustness (2004)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)THE DESIGN OF OPTIMUM MULTIFACTORIAL EXPERIMENTS (1946)On the Experimental Attainment of Optimum Conditions (1951)Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)Handbook on Constructing Composite Indicators: Methodology and User Guide (2008)How to avoid a perfunctory sensitivity analysis (2010)Tools for Composite Indicators Building (2005)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates6,377 cited
  • 1991Factorial Sampling Plans for Preliminary Computational Experiments4,936 cited
  • 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index3,567 cited
  • 2007An effective screening design for sensitivity analysis of large models2,024 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 2005Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,843 cited
  • 2004Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,797 cited
  • 2015Risk assessment and risk management: Review of recent advances on their foundation1,710 cited
  • 2015Sensitivity analysis: A review of recent advances1,172 cited
  • 2006A new uncertainty importance measure1,030 cited
  • 2015Variable importance analysis: A comprehensive review526 cited
  • 2005Reliability-based design sensitivity by efficient simulation330 cited
  • 2007Engineering computation under uncertainty – Capabilities of non-traditional models290 cited
  • 2008Subset simulation for structural reliability sensitivity analysis

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284 cited
  • 1999Sensitivity analysis: Could better methods be used?209 cited
  • Cited by

    • 2021New Importance Measures Based on Failure Probability in Global Sensitivity Analysis of Reliability44 cited
    • 2023Time-variant reliability global sensitivity analysis with single-loop Kriging model combined with importance sampling20 cited
    • 2023An improved adaptive Kriging model for importance sampling reliability and reliability global sensitivity analysis20 cited
    • 2024A novel single-loop estimation method for predictive failure probability-based global sensitivity analysis16 cited
    • 2023Reliability-based design optimization scheme of isolation capacity of nonlinear vibration isolators15 cited
    • 2022Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model15 cited
    • 2023A novel Bayesian-inference-based method for global sensitivity analysis of system reliability with multiple failure modes13 cited
    • 2024A single-loop reliability sensitivity analysis strategy for time-dependent rare events with both random variables and stochastic processes13 cited