  A study of seismic regionalization for central Chile based on a neural
network is presented. A scenario with six seismic regions is obtained,
independently of the size of the neighborhood or the reach of the correlation
between the cells of the grid. The high correlation between the spatial
distribution of the seismic zones and geographical data confirm our election of
the training vectors of the neural network.
