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Uncertainty analysis of thermoreflectance measurements
Review of Scientific Instruments, 2016We derive a generally applicable formula to calculate the precision of multi-parameter measurements that apply least squares algorithms. This formula, which accounts for experimental noise and uncertainty in the controlled model parameters, is then used to analyze the uncertainty of thermal property measurements with pump-probe thermoreflectance ...
Jia Yang, Elbara Ziade, Aaron J. Schmidt
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Uncertainty analysis in political forecasting
Decision Support Systems, 2006Medicine, engineering, and finance are traditional fields for the application of Fuzzy Logic (FL); however, in social sciences, the utilization of FL can be intensely explored as a valuable analysis instrument. Joining fuzzy with Multiple Criteria Decision Making (MCDM), the natural complex and uncertain criteria of social problems can be adequately ...
Gleiber Fernandes Royes +1 more
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Nasendoscopy: An Analysis of Measurement Uncertainties
The Cleft Palate Craniofacial Journal, 2013Objective The purpose of this study was to analyze the optical characteristics of two different nasendoscopes used to assess velopharyngeal insufficiency and to quantify the measurement uncertainties that will occur in a typical set of clinical data ...
Onur, Gilleard +4 more
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An analysis of four uncertainty calculi
IEEE Transactions on Systems, Man, and Cybernetics, 1988An important issue faced by contemporary artificial intelligence workers is how to deal with uncertain information. Four of the more prominent calculi-probability theory (especially the Bayesian approach), the Dempster-Shafer theory, fuzzy set theory, and the MYCIN and EMYCIN calculi-are examined.
Steven J. Henkind, Malcolm C. Harrison
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On Chu spaces in uncertainty analysis
International Journal of Intelligent Systems, 2000Summary: A very general algebraic framework, known as Chu spaces, has recently been systematically used in modeling of information flow in distributed systems and in modeling of concurrency in computer science. In this paper, we explore this framework in the context of uncertainty modeling and analysis.
Hung T. Nguyen 0002, Nhu T. Nguyen
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Uncertainty and Imprecision: Modelling and Analysis
Journal of the Operational Research Society, 1995Summary: Any statistical analysis or decision analysis contains numerical inputs of which we are unsure. Some of our uncertainty arises from physical randomness which we can model in various ways, ideally through probability. Some uncertainty relates to judgemental estimates of quantities about which we may be unsure in many different respects.
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Uncertainty Management and Sensitivity Analysis
2017Uncertainty is always there and LCA is no exception to that. The presence of uncertainties of different types and from numerous sources in LCA results is a fact, but managing them allows to quantify and improve the precision of a study and the robustness of its conclusions.
Rosenbaum, Ralph +2 more
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Uncertainty Analysis in River Modelling
2015Uncertainty analysis is an essential step in river modelling. Knowledge of the uncertainty is crucial for a meaningful interpretation of the model results. In this chapter we describe the whole process of an uncertainty analysis in four steps: identification, prioritization, quantification and propagation.
Warmink, Jord Jurriaan +1 more
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Investment Analysis Under Uncertainty
Management Science, 1969Investment projects are described in this paper as a pattern of uncertain cash flows over time; i.e., as a cash flow pattern over an event tree. Whereas the portfolio problem of selecting projects generally requires simultaneous consideration of all available projects, here we seek sufficient conditions for accepting and rejecting individual projects.
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