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Challenges lie in efficient monitoring, institutional support for utilities, interpretation of uncertainty by regulators, and risk communication to consumers.
This study focuses on uncertainty analysis of WWTP models and analyzes the issue of framing and how it affects the interpretation of uncertainty analysis results.
This paper investigates the classical (frequentist) and subjective (Bayesian) interpretations of uncertainty and their implications on prognostics, and argues that the Bayesian interpretation of uncertainty is more suitable for condition-based prognostics and health monitoring.
Probabilistic interpretation of uncertainty assessments is considered valuable, as the IPCC guidance note for treatment of uncertainties specifies [23].
The resulting posterior probabilities and the probabilistic interpretation of uncertainty are straightforward to communicate, as demanded in requirement 5 (intuitively understandable and straightforward to communicate).
For the discussion here, most relevant is that it is an intuitively acceptable interpretation of uncertainty as the probability of all alternative events in the sample space.
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For the illustration purpose, both Figure 9(b) and (c) are presented in 2D. Figure 9 Interpretation of resulting uncertainty in proximity analysis; (a) Deterministic proximity measure; (b) Proximity measure incorporating uncertainty in pipe location; (c) Proximity measure incorporating uncertainty in pipe location and bucket movement.
Since there is no consensus about the latter, one cannot expect consensus about the interpretation of the uncertainty relations either.
An important and interesting topic in quantum mechanics is interpretation of the uncertainty relation, which was first expounded by Heisenberg [1].
First, it may be noted that the minimal interpretation of the uncertainty relations is little more than filling in the empirical meaning of inequality (9), or an inequality in terms of other measures of width, as obtained from the standard formalism of quantum mechanics.
Future work involving interpretation of geospatial uncertainty may help to disentangle this by implementing tasks that require individuals to make judgments about larger areas of space (such as a county), which may force individuals to summarize the visualization and be less biased by individual tracks.
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