Results 251 to 260 of about 1,136,392 (299)

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.
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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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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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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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Portfolio Insurance and model uncertainty

OR Spectrum, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Modelling Uncertainty in Persuasion

2013
Participants in argumentation often have some doubts in their arguments and/or the arguments of the other participants. In this paper, we model uncertainty in beliefs using a probability distribution over models of the language, and use this to identify which are good arguments (i.e. those with support with a probability on or above a threshold).
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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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Modelling positioning uncertainties

1989
Robot programs generated by a human or by an automatic planner, must execute in a real environment which differs slightly from the model used at programming time. Thus we need to represent this uncertainty. This representation can be used at programming time to directly produce a valid program, or to verify the validity of a program afterwards.
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Modeling Uncertainty in Banking Networks

2014
Recent evidence from simulations of banking networks suggests that properties of the network design such as connectivity, bank size, or concentration affect networks’ ability to withstand stress (Arinaminpathy et al. 2012; Gai at al. 2011). However, those studies typically assume that all banks have complete knowledge about the whole system.
Stojan Davidovic, Mirta Galesic, Konstantinos V. Katsikopoulos, Nimalan Arinaminpathy   +3 more
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