The stellar parametrization using Artificial Neural Network

dc.contributor.author	Giridhar, S
dc.contributor.author	Goswami, A
dc.contributor.author	Kunder, A
dc.contributor.author	Muneer, S
dc.contributor.author	Selvakumar, G
dc.date.accessioned	2013-09-25T10:03:56Z
dc.date.available	2013-09-25T10:03:56Z
dc.date.issued	2012
dc.identifier.citation	ASI Conference Series, Vol. 6, pp. 137-142	en
dc.identifier.isbn	978-81-922926-4-9
dc.identifier.uri	http://hdl.handle.net/2248/6390
dc.description	Open Access	en
dc.description.abstract	An update on recent methods for automated stellar parametrization is given. We present preliminary results of the ongoing program for rapid parametrization of field stars using medium resolution spectra obtained using Vainu Bappu Telescope at VBO, Kavalur, India. We have used Artificial Neural Network (ANN) for estimating temperature, gravity, metallicity and absolute magnitude of the field stars. The network for each parameter is trained independently using a large number of calibrating stars. The trained network is used for estimating atmospheric parameters of unexplored field stars.	en
dc.language.iso	en	en
dc.publisher	Astronomical Society of India	en
dc.relation.uri	http://adsabs.harvard.edu/abs/2012ASInC...6..137G	en
dc.rights	© Astronomical Society of India	en
dc.subject	Stellar abundances	en
dc.subject	ANN	en
dc.subject	Absolute magnitude	en
dc.title	The stellar parametrization using Artificial Neural Network	en
dc.type	Article	en