An Application of Hierarchical Method Approach of Self Clustering Algorithm Using Self Organizing Map Neural Network

This paper describes an application of a self-clustering algorithm using hierarchical Self Organizing Map neural network. Data from different training sets are used which are compared with other optimization algorithms for preliminary calculation of the clusters' number. The results from the tests are shown in graphics. As a final result we have a well-trained network based on the topology of the data set.