Abstract
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.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Romero, C., Li, X., Keyran, S., Rossow, R.: Spectrometer-based combustion monitoring for flame stoichiometry and temperature control. Appl. Therm. Eng. 25, 659–676 (2005)
Thakur, M., Vyas, A., Shakher, C.: Measurement of temperature and temperature profile of an axisymmetric gaseous flames using lau phase interferometer with linear gratings. Opt. Laser Eng. 36, 373–380 (2001)
Lu, G., Yan, Y., Colechin, M.: A digital imaging based multifuncional flame monitoring system. IEEE T. Instrum. Meas. 53, 1152–1158 (2004)
Liu, L.H., Jiang, J.: Inverse radiation problem for reconstruction of temperature profile in axisymmetric free flames. J. Quant. Spectrosc. Radit. Transfer 70, 207–215 (2001)
McCornick, N.J.: Inverse radiative transfer problems: a review. Nuclear Science and Engineering 112, 185–198 (1992)
Eyre, J.R.: Inversion methods for satellite sounding data. Lecture Notes NWP Course. In: European Centre for Medium-Range Weather Forecasts, ECMWF (2004)
Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1999)
Pearson, K.: On lines and planes of closet fit to systems of points in space. Phil. Mag. 2, 559–572 (1901)
Hotelling, H.: Analysis of a complex of statistical variables into principal components. Educ. Physhol 24, 417–441, 498–520 (1933)
Jollife, I.T.: Principal Component Analysis, 2nd edn. Springer Series in Statistics. Springer, New York (2002)
Cybenko, G.: Approximation by superposition of a sigmoidal function. Mathematics of Control, Signals, and Systems 2, 303–314 (1989)
Hornik, K., Stinchcombe, M., White, H.: Multilayer feedforward networks are universal approximators. Neural Networks 2, 359–366 (1989)
Aires, F., Chédin, A., Scott, N.A., Rossow, W.B.: A regularized neural net approach for retrieval of atmospheric and surface temperatures with the iasi instrument. Journal of Applied Meteorology 41, 144–159 (2001)
Rothman, L.S.: The hitran molecular spectroscopic database: edition of 2000 including updates through 2001. J. Quant. Spectrosc. Radiat. Transfer (2003)
García-Cuesta, E.: CASIMIR: Cálculos Atmosfericos y Simulacion de la Transmitancia en el Infrarrojo. University Carlos III L/PFC 01781, Madrid (2003) (in Spanish)
Huang, H.L., Antonelli, P.: Application of principal component analysis to high-resolution infrared measurement compression an retrieval. J. Clim. Appl. Meteorol. 40, 365–388 (2001)
Aires, F.: Remote sensing from the infrared atmospheric sounding interferometer instrument. J. Geophys. Res. 107, ACH6–1–15 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
García-Cuesta, E., Galván, I.M., de Castro, A.J. (2006). Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_91
Download citation
DOI: https://doi.org/10.1007/11875581_91
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45485-4
Online ISBN: 978-3-540-45487-8
eBook Packages: Computer ScienceComputer Science (R0)