Genetic algorithms (GA) applied to the orthogonal projection approach (OPA) for variable selection
Genetic algorithms (GA) applied to the orthogonal projection approach (OPA) for variable selection
Multivariate curve resolution (MCR) and especially the orthogonal projection approach (OPA) can be applied to spectroscopic data and were proved to be suitable for process monitoring. To improve the quality of the on-line monitoring of batch processes, it is interesting to get as many as possible spectra in a given period of time. Nevertheless, hardware limitations could lead to the fact that it is not possible to acquire more than a certain number of spectra in this given period of time. Wavelength selection could be a good way to limit this problem since it decreases size, and consequently the acquisition time, of each recorded spectrum. This paper details an industrial application of genetic algorithms (GA) coupled with a curve resolution method (OPA) for such purpose.
Curve resolution, Genetic algorithms (GA), Orthogonal projection approach (OPA), Variable selection
11-21
Gourvénec, S.
6ff91ad8-1a91-42fe-a3f4-1b5d6f5ce0b8
Capron, X.
bad52831-9ef6-4ce5-9c4a-c76f5627d712
Massart, D. L.
e45e44fe-05dd-4936-89f0-85fe53999ce5
9 August 2004
Gourvénec, S.
6ff91ad8-1a91-42fe-a3f4-1b5d6f5ce0b8
Capron, X.
bad52831-9ef6-4ce5-9c4a-c76f5627d712
Massart, D. L.
e45e44fe-05dd-4936-89f0-85fe53999ce5
Gourvénec, S., Capron, X. and Massart, D. L.
(2004)
Genetic algorithms (GA) applied to the orthogonal projection approach (OPA) for variable selection.
Analytica Chimica Acta, 519 (1), .
(doi:10.1016/j.aca.2004.05.023).
Abstract
Multivariate curve resolution (MCR) and especially the orthogonal projection approach (OPA) can be applied to spectroscopic data and were proved to be suitable for process monitoring. To improve the quality of the on-line monitoring of batch processes, it is interesting to get as many as possible spectra in a given period of time. Nevertheless, hardware limitations could lead to the fact that it is not possible to acquire more than a certain number of spectra in this given period of time. Wavelength selection could be a good way to limit this problem since it decreases size, and consequently the acquisition time, of each recorded spectrum. This paper details an industrial application of genetic algorithms (GA) coupled with a curve resolution method (OPA) for such purpose.
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Published date: 9 August 2004
Keywords:
Curve resolution, Genetic algorithms (GA), Orthogonal projection approach (OPA), Variable selection
Identifiers
Local EPrints ID: 414622
URI: http://eprints.soton.ac.uk/id/eprint/414622
ISSN: 0003-2670
PURE UUID: e26f5f20-f616-4f9c-9f87-63af0e6784c9
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Date deposited: 05 Oct 2017 16:30
Last modified: 16 Mar 2024 04:31
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Contributors
Author:
X. Capron
Author:
D. L. Massart
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