Neural networks applied to the choice of an optimal experimental design

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.