International Journal of Computational Intelligence Systems

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Volume 13, Issue 1, 2020, Pages 1650 - 1662

Flexible Bootstrap for Fuzzy Data Based on the Canonical Representation

Authors
Przemyslaw Grzegorzewski1, 2, *, ORCID, Olgierd Hryniewicz2, Maciej Romaniuk2, 3
1Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland
2Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland
3Warsaw School of Information Technology, Newelska 6, 01-447 Warsaw, Poland
*Corresponding author. Email: p.grzegorzewski@mini.pw.edu.pl
Corresponding Author
Przemyslaw Grzegorzewski
Received 22 March 2020, Accepted 5 October 2020, Available Online 21 October 2020.
DOI
10.2991/ijcis.d.201012.003How to use a DOI?
Keywords
Ambiguity; Bootstrap; Canonical representation; Fuzziness; Fuzzy data; Fuzzy numbers; Random fuzzy numbers; Resampling
Abstract

Several new resampling methods for generating bootstrap samples of fuzzy numbers are proposed. To avoid undesired repetitions in the secondary samples we do not draw randomly directly observations from the primary samples but construct them allowing for some modifications in their membership functions, however only such which do not disturb the canonical representation of the initial fuzzy numbers. We consider both two-parameter and three-parameter canonical representations, as well as the triangular and trapezoidal outputs in the secondary samples. Numerical experiments concerning some statistical tests based on fuzzy samples show that the suggested methods may appear helpful in statistical reasoning with imprecise data.

Copyright
© 2020 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
13 - 1
Pages
1650 - 1662
Publication Date
2020/10/21
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.201012.003How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Przemyslaw Grzegorzewski
AU  - Olgierd Hryniewicz
AU  - Maciej Romaniuk
PY  - 2020
DA  - 2020/10/21
TI  - Flexible Bootstrap for Fuzzy Data Based on the Canonical Representation
JO  - International Journal of Computational Intelligence Systems
SP  - 1650
EP  - 1662
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.201012.003
DO  - 10.2991/ijcis.d.201012.003
ID  - Grzegorzewski2020
ER  -