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.
Astronomy and Astrophysics Supplement Series
- Pub Date:
- April 1996
- PLANETARY NEBULAE: GENERAL;
- METHODS: MISCELLANEOUS