Classification of planetary nebulae by cluster analysis and artificial neural networks

¹ Laboratório Nacional de Astrofísica, Caixa Postal 21, CEP:37.500-000,Itajubá, MG, Brazil
² Departamento de Física, Universidad de Santiago de Chile, Casilla 307, Correo 2, Santiago, Chile

Send offprint request to: M.  Faúndez-Abans

Received: 24 July 1995
Accepted: 18 September 1995

Abstract

According to the chemical composition, a sample of 192 Planetary Nebulae of different types has been re-classified, and 41 others have been classified for the first time, by means of two methods not employed so far in this field: hierarchical cluster analysis and supervised artificial neural network. The cluster analysis reveals itself as a good first guess for grouping Planetary Nebulae, while an artificial neural network provides reliable automated classification of this kind of objects.