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    STUDIA INFORMATICA - Issue no. 1 / 2005  
         
  Article:   A NEW DYNAMIC EVOLUTIONARY CLUSTERING TECHNIQUE. APPLICATION IN DESIGNING RBF NEURAL NETWORK TOPOLOGIES. II. NUMERICAL EXPERIMENTS.

Authors:  D. DUMITRESCU, KAROLY SIMON.
 
       
         
  Abstract:  Recently a new evolutionary optimization metaheuristics, the Genetic Chromodynamics (GC) has been proposed. Based on this meta- heuristics a dynamic clustering algorithm (GCDC) is proposed. This method is used for designing RBF neural network topologies. Complexity of these net- works can be reduced by clustering the training data. The GCDC technique is able to solve this problem. In Part I the GCDC technique is presented. It is described, how this method could be used for designing optimal RBF neural network topologies. In Part II some numerical experiments are presented. The proposed algorithm is compared with a static clustering technique, the generalized k-means algorithm.  
         
     
         
         
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