Josie McCulloch
Extending similarity measures of interval type-2 fuzzy sets to general type-2 fuzzy sets
McCulloch, Josie; Wagner, Christian; Aickelin, Uwe
Authors
Professor CHRISTIAN WAGNER Christian.Wagner@nottingham.ac.uk
PROFESSOR OF COMPUTER SCIENCE
Uwe Aickelin
Abstract
Similarity measures provide one of the core tools
that enable reasoning about fuzzy sets. While many types of
similarity measures exist for type-1 and interval type-2 fuzzy sets, there are very few similarity measures that enable the comparison of general type-2 fuzzy sets. In this paper, we introduce a general method for extending existing interval type-2 similarity measures to similarity measures for general type-2 fuzzy sets. Specifically, we show how similarity measures for interval type-2 fuzzy sets can be employed in conjunction with the zSlices based general type-2 representation for fuzzy sets to provide measures
of similarity which preserve all the common properties (i.e.
reflexivity, symmetry, transitivity and overlapping) of the original interval type-2 similarity measure. We demonstrate examples of such extended fuzzy measures and provide comparisons between (different types of) interval and general type-2 fuzzy measures.
Citation
McCulloch, J., Wagner, C., & Aickelin, U. Extending similarity measures of interval type-2 fuzzy sets to general type-2 fuzzy sets. Presented at IEEE International Conference on Fuzzy Systems 2013 (Fuzz-IEEE 2013)
Conference Name | IEEE International Conference on Fuzzy Systems 2013 (Fuzz-IEEE 2013) |
---|---|
End Date | Jul 10, 2013 |
Deposit Date | Sep 29, 2014 |
Peer Reviewed | Peer Reviewed |
Keywords | Fuzzy, Logic |
Public URL | https://nottingham-repository.worktribe.com/output/1004937 |
Publisher URL | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6622408 |
Additional Information | Published in: IEEE International Conference on Fuzzy Systems (FUZZ) 2013 (ISBN: 9781479900206 ; doi: 10.1109/FUZZ-IEEE.2013.6622408). © IEEE. |
Files
mcculloch2013.pdf
(1.1 Mb)
PDF
You might also like
Explain the world – Using causality to facilitate better rules for fuzzy systems
(2024)
Journal Article
Gradient-based Fuzzy System Optimisation via Automatic Differentiation – FuzzyR as a Use Case
(2024)
Preprint / Working Paper
Explaining time series classifiers through meaningful perturbation and optimisation
(2023)
Journal Article
Feature Importance Identification for Time Series Classifiers
(2022)
Presentation / Conference Contribution