Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/3970
COMPARTIR / EXPORTAR:
SHARE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Selection of quasar candidates from combined radio and optical surveys using neural networks |
Autor: | Carballo, R.; Cofiño, Antonio S. CSIC ORCID; González-Serrano, José Ignacio CSIC ORCID CVN | Palabras clave: | Methods: data analysis Methods: statistical Quasars: general |
Fecha de publicación: | 2004 | Editor: | Oxford University Press | Citación: | Monthly Notices of the Royal Astronomical Society 353(1): 211-220 (2004) | Resumen: | The application of supervised artificial neural networks (ANNs) for quasar selection from combined radio and optical surveys with photometric and morphological data is investigated, using the list of candidates and their classification from White et al. (2000). Seven input parameters and one output, evaluated to 1 for quasars and 0 for nonquasars, were used, with architectures 7:1 and 7:2:1. Both models were trained on samples of ~800 sources and yielded similar performance on independent test samples, with reliability as large as 87% at 80% completeness. For comparison the quasar fraction from the original candidate list was 56%. The accuracy is similar to that found by White et al. using supervised learning with oblique decision trees. This performance probably approaches the maximum value achievable with this database. Probabilities for the 98 candidates without spectroscopic classification in White et al. are presented and compared with the results from their work, showing a good agreement. This is the first analysis of the performance of ANNs for the selection of quasars. Our work shows that ANNs provide a promising technique for the selection of specific object types in astronomical databases. | Versión del editor: | http://dx.doi.org/10.1111/j.1365-2966.2004.08056.x | URI: | http://hdl.handle.net/10261/3970 | DOI: | 10.1111/j.1365-2966.2004.08056.x | ISSN: | 0035-8711 |
Aparece en las colecciones: | (IFCA) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
Selection of quasar.pdf | 393,28 kB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
WEB OF SCIENCETM
Citations
3
checked on 23-nov-2021
Page view(s)
347
checked on 19-abr-2024
Download(s)
258
checked on 19-abr-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.