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Fuzzy Relational Fixed Point Clustering
Author(s) -
Roelof K. Brouwer
Publication year - 2009
Publication title -
international journal of computational intelligence systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.385
H-Index - 41
eISSN - 1875-6891
pISSN - 1875-6883
DOI - 10.1080/18756891.2009.9727641
Subject(s) - cluster analysis , fuzzy clustering , data mining , fuzzy logic , relational database , mathematics , computer science , flame clustering , artificial intelligence , cure data clustering algorithm
The proposed relational fuzzy clustering method, called FRFP (fuzzy relational fixed point), is based on determining a fixed point of a function of the desired membership matrix. The ethod is compared to other relational clustering methods. Simulations show the method to be very effective and less computationally expensive than other fuzzy relational data clustering methods. The membership matrices that are produced by the proposed method are less crisp than those produced by NERFCM and more representative of the proximity matrix that is used as input to the clustering process.

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