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Measurement, Models, and Uncertainty

IEEE Transactions on Instrumentation and Measurement, 2012
Against the tradition, which has considered measurement able to produce pure data on physical systems, the unavoidable role played by the modeling activity in measurement is increasingly acknowledged, particularly with respect to the evaluation of measurement uncertainty.
Giordani, Alessandro, Mari, Luca Paolo
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Model Uncertainty

Mental models help people navigate complex environments. This paper studies how people deal with model uncertainty. In an experiment, participants estimate a company's value, facing uncertainty about which one of two models correctly deter- mines its true value. Using a between-subjects design, we vary the degree of model complexity.
Musolff, R., Zimmermann, F.
openaire   +4 more sources

Uncertainty in Climate Models

Science, 2002
Thomas M. Smith et al. (“how accurate are climate simulations?”, Perspectives, 19 April, p. [483][1]) suggest that today's climate models simulate the climate history of Earth over the past 150 years “within the observed uncertainty of the observations.” In comparing model results with trends in sea surface temperature in several ocean basins, they ...
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Modeling uncertainty in databases

[1991] Proceedings. Seventh International Conference on Data Engineering, 2002
Relational algebra operations were extended to produce, together with answers to queries, information regarding sources that contributed to the answers. The author's previous model is reviewed and the semantic interpretation is presented. It is shown that extended relational algebra operations are precise, that is, they produce exactly the same answers
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A Fresh Perspective on Uncertainty Modeling: Uncertainty Vs. Uncertainty Modeling

1998
It is argued that very often when talking about the uncertainty of a system people confuse the phenomena with the glasses (theories) which they use to observe or model the uncertain phenomenon. Some experts also claim, that there is only one valid theory or tool (f. i. probability theory) to model all kinds of uncertainty. In this paper it is suggested,
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MODEL UNCERTAINTY AND SCENARIO AGGREGATION

Mathematical Finance, 2014
This paper provides a coherent method for scenario aggregation addressing model uncertainty. It is based on divergence minimization from a reference probability measure subject to scenario constraints. An example from regulatory practice motivates the definition of five fundamental criteria that serve as a basis for our method.
Cambou, Mathieu, Filipović, Damir
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Portfolio Insurance and model uncertainty

OR Spectrum, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Modeling in the presence of switching uncertainties

Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066], 2001
This paper presents a method that takes into account the switching uncertainties in the signal path of the measurement devices during the identification of device models. Switching phenomena in the measurement instrument, like switching attenuators, induce jumps in the measured input-output characteristic that can be much larger than the noise ...
Wendy Van Moer   +2 more
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Finding an LFT uncertainty model with minimal uncertainty

2013 European Control Conference (ECC), 2013
In this paper, we present a procedure for finding the best LFT uncertainty model by minimizing the ℌ -infinity norm of the uncertainty set with respect to a nominal model subject to known input-output data. The main problem is how to express the data-matching constraints for convenient use in the optimization problem.
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Modeling of uncertainty

Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics, 2016
In this paper, we propose a new method of ontology fuzzification which is able to analyzing data imperfection. In general, the constituents of an ontology are, as all data from the real world, characterized by aspects of inaccuracies and uncertainties.
Houda Akremi, Sami Zghal, Gayo Diallo
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