Free Access
Issue
Analusis
Volume 26, Number 8, October 1998
Chemometrics 98
Page(s) 304 - 309
Section Original articles
DOI https://doi.org/10.1051/analusis:1998178
Analusis 26, 304-309 (1998)
DOI: 10.1051/analusis:1998178

Neural networks applied to the choice of an optimal experimental design

S. Courtois and R. Phan-Tan-Luu

L.M.R.E., Faculté des Sciences, Centre de St Jérôme, 13397 Marseille Cedex 20, France


Abstract
In the Methodology of Experimental Research (M.E.R.), the quality of the results depends on the choice of the experimental design. A lot of experimental designs exist. The goal of the presentation is to optimize the choice of an experimental design by neural networks. We present in detail the elaboration of networks which facilitates the choice of an experimental design as a second-degree model which studies six factors in the spherical experimental domain.


Key words: Methodology of Experimental Research (M.E.R.) / experimental design / neural networks with non-chaotic dynamics / learning: gradient back propagation.


© EDP Sciences, Wiley-VCH 1998

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