Journal Article10.1016/J.RESS.2017.10.007
Multivariate global sensitivity analysis for dynamic models based on wavelet analysis
Sinan Xiao,Zhenzhou Lu,Pan Wang +2 more
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TL;DR: A new kind of sensitivity indices based on wavelet analysis is proposed, which contain the information of model output in both time and frequency domains and are applied to an environmental model to tell the relative importance of the input variables, which can be useful for improving the model performance.
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About: This article is published in Reliability Engineering & System Safety. The article was published on 01 Feb 2018. The article focuses on the topics: Variance-based sensitivity analysis & Fourier amplitude sensitivity testing.
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Citations
A Bayesian Monte Carlo-based method for efficient computation of global sensitivity indices
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44
Multi-level multi-fidelity sparse polynomial chaos expansion based on Gaussian process regression
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A new efficient simulation method based on Bayes' theorem and importance sampling Markov chain simulation to estimate the failure-probability-based global sensitivity measure
TL;DR: Compared to the traditional double-loop Monte Carlo simulation method, the proposed method requires only a single set of samples to estimate the failure-probability-based global sensitivity measure and its computational cost does not depend on the dimensionality of input variables.
36
Reliability sensitivity analysis method based on subset simulation hybrid techniques
TL;DR: The results revealed that the proposed method efficiently and accurately solves rare-event, system-level, and real-world engineering problems with explicit and implicit limit state functions.
34
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