Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-10941
Authors: Hose, Dominik
Hanss, Michael
Title: On the solution of forward and inverse problems in possibilistic uncertainty quantification for dynamical systems
Issue Date: 2020
metadata.ubs.publikation.typ: Preprint
metadata.ubs.publikation.seiten: 11
URI: http://elib.uni-stuttgart.de/handle/11682/10958
http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-109583
http://dx.doi.org/10.18419/opus-10941
metadata.ubs.bemerkung.extern: Preprint submitted to 9th International Workshop on Reliable Engineering Computing REC 2021 on June 3, 2020
Abstract: In 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.
Appears in Collections:07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

Files in This Item:
File Description SizeFormat 
HoseHanss_OPUS2020.pdfPDF355,26 kBAdobe PDFView/Open


Items in OPUS are protected by copyright, with all rights reserved, unless otherwise indicated.