Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)

Consistent Inverse Probability and Possibility Propagation

Authors
Dominik Hose, Michael Hanss
Corresponding Author
Dominik Hose
Available Online August 2019.
DOI
10.2991/eusflat-19.2019.1How to use a DOI?
Keywords
Inverse Problems Probability-Possibility Consistency Imprecise Probabilities Uncertainty Propagation Possibility Theory
Abstract

Given a probability distribution of an output quantity of a model, it is generally not possible to infer a unique probability distribution of the uncertain input quantity. In this contribution, it is shown that by reverting back to the coarser framework of possibility theory this problem possesses a conceptually straightforward solution with some powerful properties in the view of imprecise probability descriptions.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
Series
Atlantis Studies in Uncertainty Modelling
Publication Date
August 2019
ISBN
978-94-6252-770-6
ISSN
2589-6644
DOI
10.2991/eusflat-19.2019.1How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Dominik Hose
AU  - Michael Hanss
PY  - 2019/08
DA  - 2019/08
TI  - Consistent Inverse Probability and Possibility Propagation
BT  - Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
PB  - Atlantis Press
SP  - 1
EP  - 8
SN  - 2589-6644
UR  - https://doi.org/10.2991/eusflat-19.2019.1
DO  - 10.2991/eusflat-19.2019.1
ID  - Hose2019/08
ER  -