Book ChapterDOI
Sobol Indices for Dimension Adaptivity in Sparse Grids
R.P. Dwight,S.G.L. Desmedt,P. Shoeibi Omrani +2 more
- pp 371-395
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TLDR
Sobol indices can be used to perform dimension adaptivity to mitigate computational costs further, and is compared to conventional adaptation schemes on sparse grids and seen to perform comparably, without requiring the expense associated with a look-ahead error estimate.Abstract:
Propagation of random variables through computer codes of many inputs is primarily limited by computational expense. The use of sparse grids mitigates these costs somewhat; here we show how Sobol indices can be used to perform dimension adaptivity to mitigate them further. The method is compared to conventional adaptation schemes on sparse grids (Gerstner and Griebel, Computing 71(1), 65–87, 2003), and seen to perform comparably,without requiring the expense associated with a look-ahead error estimate. It is demonstrated for an expensive computer model of contaminant flow over a barrier.read more
Citations
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TL;DR: Through parametric sensitivity analysis and uncertainty quantification of the CovidSim model, a subset of this model’s parameters is identified to which the code output is most sensitive, allowing better and more informed decisions about proposed policies.
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References
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Journal ArticleDOI
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