Processing of spectrophotometric array signals using an artificial intelligence method

DOI

10.2991/iccsee.2013.312How to use a DOI?

Keywords

Least squares support vector machines, Genetic algorithms, Spectrophotometric array signals, Overlapping spectra, Artificial intelligence

Abstract

This paper addresses processing of spectrophotometric array signals based on genetic algorithms (GA) least square support vector machines (LS-SVM) regression to provide a powerful model for machine learning and data mining. The key to complete LS-SVM regression is to choose its optimal parameters. Due to their outstanding ability in solving global optimization problems in complex multidimensional search space, GA are used in this study to obtain the optimal parameter combination of the LS-SVM model. Experimental results showed the GA-LS-SVM method to be successful for simultaneous multicomponent determination even where severe overlap of spectra was present.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ling Gao
AU  - Shouxin Ren
PY  - 2013/03
DA  - 2013/03
TI  - Processing of spectrophotometric array signals using an artificial intelligence method
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 1243
EP  - 1246
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.312
DO  - 10.2991/iccsee.2013.312
ID  - Gao2013/03
ER  -