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On the other hand, uncertainty studies require repetitious usage of the analytical calculation.
The results of these uncertainty studies are optimal values of permeabilities described by fuzzy sets.
The method, therefore, is ideally suited for optimization and uncertainty studies.
These in silico results were supported by other model structures (M7, M8 and M9 at Supplementary 3) and parameter uncertainty studies (Supplementary 4).
Uncertainty studies and reliability assessments have become important topics/areas in geotechnical engineering, and different site-characterization approaches have been developed in an attempt to incorporate the sources of uncertainty into the analysis.
A set of uncertainty studies will: 1) evaluate key uncertainties in the ocean that help explain decadal variability; 2) examine predictability of hydrologic response to climate change especially as it affects power generation (hydroelectricity, power plant cooling); and 3) assess vulnerability of the grid to extreme events and links to decision-making under uncertainty.
Major remaining challenges are standardization of approaches to quantifying uncertainty in model structure, parameters and inputs, going beyond studies of specific sources of uncertainty to estimation of overall prediction uncertainty, comparing and combining validation and uncertainty studies, and evaluation of uncertainty estimates.
Extensive uncertainty studies are allocated in [14] and [15] to conduct the distributed energy resources (DERs) impacts on distribution systems.
In the event of uncertainty, studies were included for full-text review.
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Then, the prediction accuracy and the optimal separation robustness, including the uncertainty study, were evaluated.
We illustrate this workflow in a pre-injection uncertainty study for the Illinois Basin Decatur Project IBDPP).
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