{epistemic and aleatory uncertainty {constraints and priors {models all the way down {Freedman’s Rabbit-Hat theorem {hierarchical priors {the ludic fallacy {rates versus probabilities {theories of probability {probability as metaphor {responsible quanti cation v. quantifauxcation 9 6 Aleatory Uncertainty and Epistemic Uncertainty • Aleatory uncertainty is an inherent variation associated with the physical system or the environment – Also referred to as variability, irreducible uncertainty, and stochastic uncertainty, random uncertainty • Examples: – Variation in atmospheric conditions and angle of attack for inlet conditions – Variation in fatigue life of ... Uncertainty Quantification (UQ) is the theoretical and computational fabric that connects the three pillars of science – theory, experimentation, and computation – through which uncertainties are characterized and informed to guide the scientific discovery and decision-making process. Description. Dakota provides a variety of methods for propagating both aleatory and epistemic uncertainty. At a high level, uncertainty quantification (UQ) or nondeterministic analysis is the process of characterizing input uncertainties, forward propagating these uncertainties through a computational model, and performing statistical or interval assessments on the resulting responses. The aleatory uncertainty refers to natural variation and is hard to be avoided, while the epistemic uncertainty is originated from the lack of knowledge and approximations made in the modeling ... Quantification of the epistemic and aleatory uncertainty (Roy and Oberkampf, 2011). Validation metrics can be computed with help of a p-box ( Roy and Oberkampf, 2011 ). If the original (full model) is computationally expensive, then a surrogate modeling approach can be used for the quantification of uncertainty. Epistemic uncertainty quantification methods. In literature, the most common methods of modeling epistemic uncertainty are the following. Bayesian probability is a method that appoints a frequency or probability of an event, based on an educated guess or a personal belief.; Evidence theory, also known and as Dempster-Shafer theory or theory of belief functions. Introduction Uncertainty quantification (UQ) has become a hot topic in virtually all domains of applied sciences and engineering in the last decade. In the research community, this relatively new field lies at the boundary of applied mathematics, statistics, and computational engineering sciences. In the last few years, not only the number of scientific publications in this area has blown up ... The main objective of the UQ study in AM is to reduce epistemic uncertainty towards reliable quantification of the aleatory uncertainty and to determine how aleatory uncertainties from different ... Uncertainty quantification for multilabel text classification. Wenshi Chen. College of Information Science and Technology, Dalian Maritime University, Dalian, China. ... the aleatory uncertainty of each classification label and the epistemic uncertainty of the prediction result can further be obtained by this framework. We design experiments to ...
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