An exploration of alternative approaches to the representation of uncertainty in model predictions

By Jon C. Helton, Jay D. Johnson, William Oberkampf. 2003

414 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Control and Systems Engineering, Statistics and Probability

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Citations in the corpus

Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI (2020, background): “Uncertainty is often described as a single concept, although several authors have made attempts to categorize different kinds of uncertainty.(30,31) Weisberg(32) divides uncertainty into components of doubt and ambiguity; doubt may be quantified as a probability”
Sensitivity in risk analyses with uncertain numbers. (2006, background): “…(Oberkampf and Helton 2005), reliability studies for dikeworks (Hall and Lawry 2001), competing failure calculations for strong/weak link switches (Helton et al. 2004a; 2005b; 2006a); automotive design (Rekuc et al. 2006), aircraft reliability (Tonon et al. 1999); global warming (Kriegler and…”
Imprecise probabilities in engineering analyses (2013, neutral): “The proposed solution concepts include a combination of probability theory, evidence theory, possibility theory and interval analysis [20], probability bounds analysis [61], distribution envelope determination [60], sets of probability measures [59], coherent lower and upper probabilities [58], impr”
Survey of sampling-based methods for uncertainty and sensitivity analysis (2006, methodology): “(6-86) with grid for SI test with nI = nD = 5 (adapted from Fig.”
Component Models for Fuzzy Data (2006, background): “Although uncertainty of type (i) is usually dealt with by means of a probability model (describing the data generation process), this approach may not be suitable for coping with other kinds of uncertainty such as vagueness, imprecision, partial ignorance ( Helton, Johnson, & Oberkampf, 2004 ).”
Aleatoric and epistemic uncertainty in groundwater flow and transport simulation (2009, methodology): “[3] Despite these apparent distinctions in uncertainty, probability theory alone has traditionally been used to characterize both forms of uncertainty in engineering applications [Apostolakis, 1990; Helton et al., 2004].”
Reliability-based design optimization of multidisciplinary system under aleatory and epistemic uncertainty (2016, background): “poorly known quantity (Baudrit and Dubois 2006) or with reference to a deterministic but poorly known physical quantity (Helton et al. 2004).”