A definition for I-fuzzy partitions

Authors:
Vicenç Torra;Sadaaki Miyamoto
Affiliations:
CSIC, Spanish Council for Scientific Research, IIIA, Institut d’Investigació en Intel-ligència Artificial, Campus de Bellaterra, 08193, Bellaterra, Catalonia, Spain;University of Tsukuba, Department of Risk Engineering, School of Systems and Information Engineering, 305-8573, Tsukuba, Ibaraki, Japan
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Year:
2011

Citing 0
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Applying I-Fuzzy Partitions to Represent Sets of Fuzzy Partitions

Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Intuitionistic fuzzy hypergraphs with applications

Information Sciences: an International Journal

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Abstract

In this paper, we define I-fuzzy partitions (or intuitionistic fuzzy partitions as called by Atanassov or interval-valued fuzzy partitions). As our ultimate goal is to compare the results of standard fuzzy clustering algorithms (e.g. fuzzy c-means), we define a method to construct them from a set of fuzzy clusters obtained from several executions of fuzzy c-means. From a practical point of view, the approach presented here tries to solve the difficulty of comparing the results of fuzzy clustering methods and, in particular, the difficulty of finding the global optimal.