THE STUDY FOR OPTIMIZATION OF CHROMATOGRAPHIC CONDITION BY MEANS OF ARTIFICIAL NEURAL NETWORKS

Authors
GUO WQ ZHU P BRODOWSKY H
Citation
Wq. Guo et al., THE STUDY FOR OPTIMIZATION OF CHROMATOGRAPHIC CONDITION BY MEANS OF ARTIFICIAL NEURAL NETWORKS, Talanta, 44(11), 1997, pp. 1995-2001
Citations number
22
Journal title
Talanta
ISSN journal
00399140 → ACNP
Volume
44
Issue
11
Year of publication
1997
Pages
1995 - 2001
Database
ISI
SICI code
0039-9140(1997)44:11<1995:TSFOOC>2.0.ZU;2-I
Abstract
In this paper, the optimization of gas chromatographic experimental pa rameters is investigated using a three layer feed-forward neural netwo rk 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. Netw ork results are compared with the results obtained by the orthogonal m ethod. (C) 1997 Elsevier Science B.V.