A new hybrid approach for data clustering

2010 5th International Symposium on Telecommunications, IST 2010

Volumn , Issue , 2010, Pages 914-919

  Yazdani, Danial ^a   Golyari, Sara ^a   Meybodi, Mohammad Reza ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Artificial fishes swarm algorithm; Data clustering; K means; Optimization; PSO

Indexed keywords

ARTIFICIAL FISH; CLUSTERING APPROACH; CLUSTERING PROBLEMS; CONVERGENT RATE; DATA CLUSTERING; DATA SETS; HYBRID APPROACH; HYBRID CLUSTERING; INITIAL POINT SENSITIVITY; INITIAL VALUES; ITS EFFICIENCIES; K-MEANS; K-MEANS ALGORITHM; LOCAL OPTIMAL; MACHINE-LEARNING; OPTIMIZATION PROBLEMS; PSO; SWARM ALGORITHMS; SWARM INTELLIGENT;

CLUSTER ANALYSIS; CONVERGENCE OF NUMERICAL METHODS; FISH; PARTICLE SWARM OPTIMIZATION (PSO); PATTERN RECOGNITION; PROBLEM SOLVING; WIRELESS SENSOR NETWORKS;

CLUSTERING ALGORITHMS;

EID: 79953868840     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISTEL.2010.5734153     Document Type: Conference Paper

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