2012
DOI: 10.1155/2012/617481
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Epistemic Uncertainty Analysis: An Approach Using Expert Judgment and Evidential Credibility

Abstract: When dealing with complex systems, all decision making occurs under some level of uncertainty. This is due to the physical attributes of the system being analyzed, the environment in which the system operates, and the individuals which operate the system. Techniques for decision making that rely on traditional probability theory have been extensively pursued to incorporate these inherent aleatory uncertainties. However, complex problems also typically include epistemic uncertainties that result from lack of kn… Show more

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Cited by 11 publications
(9 citation statements)
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“…In order to properly address this issue we considered OQR and FQR (Bello et al, 2021) and the seismological formal errors derived from our analyses (Seismological Data and Analysis; Supplementary Figure S5; Supplementary Tables S1, S2). Specifically, the two quality factors used to constrain the faults at the surface together with the high-sampling step (as recently suggested by Sgambato et al, 2020) helped reducing the subjectivity in the interpretation (e.g., Bond et al, 2007;Bond et al, 2011;Hester, 2012;Salisbury et al, 2015). With our approach it is possible to discern and further select the objective and subjective parts of our final model.…”
Section: Geometric Fault Modelmentioning
confidence: 95%
“…In order to properly address this issue we considered OQR and FQR (Bello et al, 2021) and the seismological formal errors derived from our analyses (Seismological Data and Analysis; Supplementary Figure S5; Supplementary Tables S1, S2). Specifically, the two quality factors used to constrain the faults at the surface together with the high-sampling step (as recently suggested by Sgambato et al, 2020) helped reducing the subjectivity in the interpretation (e.g., Bond et al, 2007;Bond et al, 2011;Hester, 2012;Salisbury et al, 2015). With our approach it is possible to discern and further select the objective and subjective parts of our final model.…”
Section: Geometric Fault Modelmentioning
confidence: 95%
“…There are sources of both aleatory and epistemic uncertainty in the VS measurements 63 . While the aleatory uncertainty is considered to be irreducible, inherent and due to chance, the epistemic uncertainty is considered to be reducible, subjective and due to lack of knowledge 66 , 67 . The sources of these uncertainties are manifold.…”
Section: Technical Validationmentioning
confidence: 99%
“…Despite this accuracy of prediction, the high variability has led to uncertainty mainly due to the data scarcity and volatility of energy markets. Addressing this uncertainty of prediction has been researched in several other domains, and it can be theorised into two aspects, aleatory uncertainty and epistemic uncertainty [47]. Aleatory uncertainty is an uncertainty due to chance, also known as stochastic uncertainty, and it cannot be resolved with more data.…”
Section: Time-series Forecasting and Uncertainty Metricsmentioning
confidence: 99%