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A Comparative Review of Sensitivity and Uncertainty Analysis of Large-Scale Systems—I: Deterministic Methods
2 references·16 citing·44 second hop
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this work references cited by second hop

References

  • 2003Sensitivity & Uncertainty Analysis, Volume 1344 cited
  • 2000Measurement Errors and Uncertainties126 cited

Cited by

  • 2012Sensitivity analysis of TOPSIS method in water quality assessment: I. Sensitivity to the parameter weights137 cited
  • 2012Update 1 of: Sensitivity Analysis for Chemical Models92 cited
  • 2011Quantification of margins and uncertainties: Conceptual and computational basis87 cited
  • 2021Sensitivity analysis of the integrated AHP-TOPSIS and CRITIC-TOPSIS method for selection of the natural fiber65 cited
  • 2021Selection of the natural fiber for sustainable applications in aerospace cabin interior using fuzzy MCDM model59 cited
  • 2008Uncertainty and Sensitivity Analysis for Models of Complex Systems57 cited
  • 2013Grid and basis adaptive polynomial chaos techniques for sensitivity and uncertainty analysis52 cited
  • 2020Basic Framework and Main Methods of Uncertainty Quantification52 cited
  • 2017Borgonovo moment independent global sensitivity analysis by Gaussian radial basis function meta-model47 cited
  • 2006Survey of sampling-based methods for uncertainty and sensitivity analysis.44 cited
  • 2011Quantification of margins and uncertainties: Example analyses from reactor safety and radioactive waste disposal involving the separation of aleatory and epistemic uncertainty42 cited

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2016
Inverse uncertainty quantification of reactor simulations under the Bayesian framework using surrogate models constructed by polynomial chaos expansion
34 cited
  • 2013Regional sensitivity analysis using revised mean and variance ratio functions34 cited
  • 2015Assessment of global sensitivity analysis methods for project scheduling21 cited
  • 2014Efficient Sensitivity Analysis of Structures with Local Modifications. I: Time Domain Responses17 cited
  • 2009Inverse probabilistic modelling of the sources of uncertainty: a non-parametric simulated-likelihood method with application to an industrial turbine vibration assessment15 cited