The study for optimization of chromatographic condition by means of artificial neural networks

W Guo; P Zhu; H Brodowsky

doi:10.1016/s0039-9140(96)02171-6

The study for optimization of chromatographic condition by means of artificial neural networks

Talanta. 1997 Nov;44(11):1995-2001. doi: 10.1016/s0039-9140(96)02171-6.

Authors

W Guo¹, P Zhu, H Brodowsky

Affiliation

¹ Department of Chemistry, Hangzhou University, Hangzhou, 310028, People's Republic of China.

PMID: 18966945
DOI: 10.1016/s0039-9140(96)02171-6

Abstract

In this paper, the optimization of gas chromatographic experimental parameters is investigated using a three layer feed-forward neural network with the back-propagating. The design, development, and testing of the neural network are described in detail. The chosen structure is 4-6-2 system with a learning rate eta of 0.6 and a momentum constant mu of 0.4. The results of several simulations are very satisfactory. Network results are compared with the results obtained by the orthogonal method.