RT Conference Proceedings
T1 Spectral high resolution feature selection for retrieval of combustion temperature profiles
A1 García-Cuesta, Esteban
A1 Galván, Inés M.
A1 Castro, Antonio J. de
AB The use of high spectral resolution measurements to obtain a retrieval of certain physical properties related with the radiative transfer of energy leads a priori to a better accuracy. But this improvement in accuracy is not easy to achieve due to the great amount of data which makes difficult any treatment over it and it's redundancies. To solve this problem, a pick selection based on principal component analysis has been adopted in order to make the mandatory feature selection over the different channels. In this paper, the capability to retrieve the temperature profile in a combustion environment using neural networks jointly with this spectral high resolution feature selection method is studied.
PB Springer
SN ISBN 978-3-540-45485-4
SN 0302-9743 (Print)
SN 1611-3349 (Online)
YR 2006
FD 2006
LK http://hdl.handle.net/10016/4470
UL http://hdl.handle.net/10016/4470
LA eng
NO Proceeding of: 7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006 (Burgos, Spain, September 20-23, 2006)
DS e-Archivo
RD 28 abr. 2024