Computer Science – Artificial Intelligence
Scientific paper
Jul 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994ap%26ss.217..139w&link_type=abstract
Astrophysics and Space Science (ISSN 0004-640X), vol. 217, no. 1-2, p. 139-140
Computer Science
Artificial Intelligence
Artificial Intelligence, Astronomical Catalogs, Infrared Astronomy, Stars, Stellar Spectra, Astronomical Spectroscopy, Classifications, Infrared Astronomy Satellite, Infrared Spectrometers, Line Spectra, Statistical Analysis, Stellar Envelopes
Scientific paper
The Infrared Astronomy Satellite (IRAS) Low Resolution Spectrometer (LRS) covered the spectral region from 7 micrometers to 23 micrometers; and an Atlas was produced containing 5425 spectra. Most of the spectra were associated with evolved stars, including over 3000 spectra from the dust shells around O-rich stars. When Artificial Intelligence techniques were applied to the dataset, a new classification was derived. A scheme with 77 classes, grouped into 9 metaclasses, resulted, and for those types of spectra which were well represented in the initial dataset (i.e., the evolved stars) a very subtle classification was derived, often using line shapes, relative line strengths, or the presence of additional weak features.
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