| Title:
|
Non-stochastic uncertainty quantification of a multi-model response () |
| Author:
|
Chleboun, Jan |
| Language:
|
English |
| Journal:
|
Programs and Algorithms of Numerical Mathematics |
| Volume:
|
Proceedings of Seminar. Hejnice, June 23-28, 2024 |
| Issue:
|
2024 |
| Year:
|
|
| Pages:
|
41-50 |
| . |
| Category:
|
math |
| . |
| Summary:
|
The focus is put on the application of fuzzy sets and Dempster-Shafer theory in assessing the nature and extent of uncertainty in the response of $M$ models that model the same phenomenon and depend on fuzzy input data. Dempster-Shafer theory uses a weighted family of fixed sets called the focal elements to evaluate the relationship between an arbitrarily chosen set and the focal elements. It is proposed to create at least $M$ weighted focal elements on the basis of 1) the responses to fuzzy inputs to the models, and 2) the weights associated with the models. Four variants of this approach are illustrated by academic examples. (English) |
| Keyword:
|
fuzzy sets |
| Keyword:
|
evidence theory |
| Keyword:
|
uncertainty |
| MSC:
|
03E75 |
| MSC:
|
90C90 |
| DOI:
|
10.21136/panm.2024.04 |
| . |
| Date available:
|
2025-06-02T07:39:22Z |
| Last updated:
|
2025-06-05 |
| Stable URL:
|
http://hdl.handle.net/10338.dmlcz/703222 |
| . |
