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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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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 -