A. Forti, (2006) Growing hierarchical tree SOM: An unsupervised neural network with dynamic topology, , Gian Luca Foresti, Neural Networks, 19, 1568–1580.

has been cited by the following article:

• TITLE: Application of SOM neural network in clustering

  AUTHORS: Soroor Behbahani, Ali Moti Nasrabadiv

  KEYWORDS: SOM Neural Network; Feature; Clustering; Animal

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.2 No.8, December 15, 2009

  ABSTRACT: The Self-Organizing Map (SOM) is an unsupervised neural network algorithm that projects high-dimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map. One of the SOM neural network’s applications is clustering of animals due their features. In this paper we produce an experiment to analyze the SOM in clustering different species of animals.