07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
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Item Open Access Possibilistic calculus as a conservative counterpart to probabilistic calculus(2019) Hose, Dominik; Hanss, MichaelIn this contribution, we revisit Zadeh's Extension Principle in the context of imprecise probabilities and present two simple modifications to obtain meaningful results when using possibilistic calculus to propagate credal sets of probability distributions through models. It is demonstrated how these results facilitate the possibilistic solution of two benchmark problems in uncertainty quantification.Item Open Access On data-based estimation of possibility distributions(2019) Hose, Dominik; Hanss, MichaelIn this paper, we show how a possibilistic description of uncertainty arises very naturally in statistical data analysis. In combination with recent results in inverse uncertainty propagation and the consistent aggregation of marginal possibility distributions, this estimation procedure enables a very general approach to possibilistic identification problems in the framework of imprecise probabilities, i.e. the non-parametric estimation of possibility distributions of uncertain variables from data with a clear interpretation.Item Open Access On the solution of forward and inverse problems in possibilistic uncertainty quantification for dynamical systems(2020) Hose, Dominik; Hanss, MichaelIn this contribution, we adress an apparent lack of methods for the robust analysis of dynamical systems when neither a precise statistical nor an entirely epistemic description of the present uncertainties is possible. Relying on recent results of possibilistic calculus, we revisit standard prediction and filtering problems and show how these may be solved in a numerically exact way.