Solutions to problems with imprecise data - an engineering perspective to generalized uncertainty models.

S. Pannier, M. Waurick, W. Graf, M. Kaliske

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

The present paper is about data corrupted by both aleatoric and epistemic uncertainty. A unification of randomness, which represents aleatoric uncertainty, and fuzziness, which represents epistemic uncertainty, is dicussed in detail. As a result, the main uncertainty characteristics, i.e., variability, incompleteness and imprecision, can be described. With a focus on engineering problems the aim is to bridge the imprecision of data to the decision making process. Suitable fields of applications are highlighted; remarks on the numerical treatment are given.
LanguageEnglish
Pages105-120
Number of pages16
JournalMechanical Systems and Signal Processing
Volume37
Issue number1-2
Early online date27 Sep 2012
DOIs
Publication statusPublished - 30 Jun 2013

Fingerprint

Epistemic Uncertainty
Imprecise Data
Imprecision
Model Uncertainty
Engineering
Uncertainty
Incompleteness
Fuzziness
Unification
Randomness
Decision Making
Decision making

Keywords

  • fuzzy probability based fuzzy randomness
  • generalized uncertainty models
  • fuzzy randomness
  • fuzzy probability
  • imprecise data

Cite this

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Solutions to problems with imprecise data - an engineering perspective to generalized uncertainty models. / Pannier, S.; Waurick, M.; Graf, W.; Kaliske, M.

In: Mechanical Systems and Signal Processing, Vol. 37, No. 1-2, 30.06.2013, p. 105-120.

Research output: Contribution to journalArticle

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