Determining the most proper number of cluster in fuzzy clustering by using artificial neural networks

Expert Systems with Applications

Volumn 38, Issue 3, 2011, Pages 2248-2252

  Alp Erilli, N ^a   Yolcu, Ufuk ^a   Eǧrioǧlu, Erol ^a   Hakan Aladag C ^b   Öner, Yüksel ^a  

^a ONDOKUZ MAYIS UNIVERSITY   (Turkey)

^b HACETTEPE UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Cluster validation index; Fuzzy clustering; Number of cluster

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CLUSTER VALIDATION; CLUSTER VALIDATION INDICES; CLUSTERING ANALYSIS; CLUSTERING PROBLEMS; DETERMINING THE NUMBER OF CLUSTERS; MEMBERSHIP DEGREES; NUMBER OF CLUSTERS; PRE-INFORMATION; VALIDATION INDEX;

CLUSTERING ALGORITHMS; FUZZY CLUSTERING; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS;

CLUSTER ANALYSIS;

EID: 78049529962     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.08.012     Document Type: Article

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