Classification of planetary nebulae by cluster analysis and artificial neural networks
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
Accepted: 18 September 1995
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.
Key words: planetary nebulae: general / methods: miscellaneous
© European Southern Observatory (ESO), 1996