Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-10429
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dc.contributor.authorHose, Dominik-
dc.contributor.authorHanss, Michael-
dc.date.accessioned2019-07-04T14:41:02Z-
dc.date.available2019-07-04T14:41:02Z-
dc.date.issued2019de
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/10446-
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-104468de
dc.identifier.urihttp://dx.doi.org/10.18419/opus-10429-
dc.description.abstractIn 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.en
dc.language.isoende
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.subject.ddc510de
dc.titlePossibilistic calculus as a conservative counterpart to probabilistic calculusen
dc.typepreprintde
ubs.bemerkung.externPreprint submitted to Mechanical Systems and Signal Processing on May 24, 2019.de
ubs.fakultaetKonstruktions-, Produktions- und Fahrzeugtechnikde
ubs.institutInstitut für Technische und Numerische Mechanikde
ubs.publikation.noppnyesde
ubs.publikation.seiten12de
ubs.publikation.typPreprintde
Appears in Collections:07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

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