A new fuzzy set merging technique using inclusion-based fuzzy clustering

Nefti-Meziani, S; Kaymak, U; Oussalah, M

Abstract

This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzzy set in the cluster prototypes. The merger method is applied to fuzzy rule base simplification by automatically replacing the fuzzy sets corresponding to a given cluster with that pertaining to cluster prototype. The feasibility and the performance of the proposed method are studied using an application in mobile robot navigation. The results indicate that the proposed merging and rule base simplification approach leads to good navigation performance in the application considered and to fuzzy models that are interpretable by experts. In this paper, we concentrate mainly on fuzzy systems with Gaussian membership functions, but the general approach can also be applied to other parameterized fuzzy sets.

Citation

Nefti-Meziani, S., Kaymak, U., & Oussalah, M. (2008). A new fuzzy set merging technique using inclusion-based fuzzy clustering. https://doi.org/10.1109/TFUZZ.2007.902011

• Journal Article Type: Article
• Publication Date: Feb 1, 2008
• Deposit Date: Jan 9, 2009
• Publicly Available Date: Jan 9, 2009
• Journal: Fuzzy Systems, IEEE Transactions on
• Print ISSN: 10636706
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 1
• Pages: 145-161
• DOI: https://doi.org/10.1109/TFUZZ.2007.902011
• Keywords: Fuzzy set theory, mobile robots, path planning, pattern clustering, fuzzy rule base simplification, fuzzy set merging technique, inclusion-based fuzzy clustering, mobile robot navigation, fuzzy clustering, fuzzy modeling, fuzzy sets, inclusion, merging
• Publisher URL: http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4358807
• Related Public URLs: http://ieeexplore.ieee.org/Xplore/dynhome.jsp