SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions
16 references·8 citing·34 second hop
Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions (2017)Efficient design of experiments for sensi…A Review on Global Sensitivity Analysis Methods (2015)A Review on Global Sensitivit…How to avoid a perfunctory sensitivity analysis (2010)How to avoid a perfunctory se…Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)Efficient computation of glob…Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis (2010)Convergence and uncertainty a…An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis (2009)An adaptive algorithm to buil…Global Sensitivity Analysis: The Primer by Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, Stefano Tarantola (2008)Global Sensitivity Analysis: …Calculations of Sobol indices for the Gaussian process metamodel (2008)Calculations of Sobol indices…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…Stochastic finite element: a non intrusive approach by regression (2006)Stochastic finite element: a …Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)A Comparison of Three Methods…Bayesian Experimental Design: A Review (1995)Bayesian Experimental Design:…Optimal Discretization of Random Fields (1993)Optimal Discretization of Ran…Factorial Sampling Plans for Preliminary Computational Experiments (1991)Factorial Sampling Plans for …Nonlinear sensitivity analysis of multiparameter model systems (1978)Nonlinear sensitivity analysi…Active Learning of Ensemble Polynomial Chaos Expansion Method for Global Sensitivity Analysis (2024)Active Learning of Ensemble P…Robust adaptive least squares polynomial chaos expansions in high‐frequency applications (2023)Robust adaptive least squares…Global sensitivity analysis using polynomial chaos expansion enhanced Gaussian process regression method (2023)Global sensitivity analysis u…Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification (2022)Arbitrary multi-resolution mu…Risk of estimators for Sobol’ sensitivity indices based on metamodels (2021)Risk of estimators for Sobol’…A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design (2021)A hybrid sequential sampling …Robust adaptive least squares polynomial chaos expansions in high‐frequency applications (2020)Robust adaptive least squares…An efficient local search-based genetic algorithm for constructing optimal Latin hypercube design (2019)An efficient local search-bas…Design and Analysis of Computer Experiments (1989)Random forests for global sensitivity analysis: A selective review (2020)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization (2022)Applied Statistical Decision Theory (1962)Theory of optimal experiments (1972)Kriging metamodeling in simulation: A review (2007)Response surface methodology (2010)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Stochastic Finite Elements: A Spectral Approach (1991)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)UQLab: A Framework for Uncertainty Quantification in Matlab (2014)Structural Reliability under Incomplete Probability Information (1986)Uncertainties in probabilistic numerical analysis of structures and solids-Stochastic finite elements (1997)Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes (2001)The PHI2 method: a way to compute time-variant reliability (2003)Structural Reliability Methods (1996)Reliability-based design optimization using kriging surrogates and subset simulation (2011)A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)LIF: A new Kriging based learning function and its application to structural reliability analysis (2016)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)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)A review of techniques for parameter sensitivity analysis of environmental models (1994)Importance measures in global sensitivity analysis of nonlinear models (1996)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)From screening to quantitative sensitivity analysis. A unified approach (2011)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)A new uncertainty importance measure (2006)
this work references cited by second hop

References

  • 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code8,233 cited
  • 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
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 1995Bayesian Experimental Design: A Review1,846 cited
  • 2015A Review on Global Sensitivity Analysis Methods1,113 cited
  • 2010How to avoid a perfunctory sensitivity analysis1,000 cited
  • 2009An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis834 cited
  • 1993Optimal Discretization of Random Fields728 cited
  • 1978Nonlinear sensitivity analysis of multiparameter model systems696 cited
  • 2008Global Sensitivity Analysis: The Primer by Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, Stefano Tarantola511 cited
  • 2006Stochastic finite element: a non intrusive approach by regression427 cited
  • 2010Efficient computation of global sensitivity indices using sparse polynomial chaos expansions383 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2008Calculations of Sobol indices for the Gaussian process metamodel331 cited
  • 2010Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis326 cited
  • Cited by

    • 2019An efficient local search-based genetic algorithm for constructing optimal Latin hypercube design47 cited
    • 2024Active Learning of Ensemble Polynomial Chaos Expansion Method for Global Sensitivity Analysis32 cited
    • 2021A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design19 cited
    • 2022Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification18 cited
    • 2023Robust adaptive least squares polynomial chaos expansions in high‐frequency applications18 cited
    • 2020Robust adaptive least squares polynomial chaos expansions in high‐frequency applications16 cited
    • 2023Global sensitivity analysis using polynomial chaos expansion enhanced Gaussian process regression method12 cited
    • 2021Risk of estimators for Sobol’ sensitivity indices based on metamodels8 cited