Naslov
Application of different training methodologies for the development of a back propagation artificial neural network retention model in ion chromatography

Autori
Bolanča, Tomislav ; Cerjan Stefanović, Štefica ; Ukić, Šime ; Rogošić, Marko ; Luša, Melita

Izvornik
Journal of chemometrics (0886-9383) 22 (2008), 1-2; 106-113

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
artificial neural network ; training algorithm ; retention modeling ; ion chromatography

Sažetak
The reliability of predicted separations in ion chromatography depends mainly on the accuracy of retention predictions. Any model able to improve this accuracy will yield predicted optimal separations closer to the reality. In this work artificial neural networks were used for retention modeling of void peak, fluoride, chlorite, chloride, chlorate, nitrate and sulfate. In order to increase performance characteristics of the developed model, different training methodologies were applied and discussed. Furthermore, the number of neurons in hidden layer, activation function and number of experimental data used for building the model were optimized in terms of decreasing the experimental effort without disruption of performance characteristics. This resulted in the superior predictive ability of developed retention model (average of relative error is 0.4533%).

Izvorni jezik
Engleski

Znanstvena područja
Kemijsko inženjerstvo

POVEZANOST RADA