Naslov
Application of Artificial Neural Network and Multiple Linear Regression Retention Models for Optimization of Separation in Ion Chromatography by Using Several Criteria Functions

Autori
Bolanča, Tomislav ; Cerjan-Stefanović, Štefica ; Novič, Milko

Izvornik
Chromatographia (0009-5893) 61 (2005); 181-187

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

Ključne riječi
Column liquid chromatography; Ion chromatography; Criteria functions; Empirical retention modelling

Sažetak
This work focuses on problems regarding empirical retention modelling and optimization of separation in ion chromatography. Influences of eluent flow rate and concentration of eluent competing ion (OH-) on separation of seven inorganic anions (fluoride, chloride, nitrite, sulphate, bromide, nitrate, and phosphate) were investigated. Artificial neural networks and multiple linear regression retention models in combination with several criteria functions were used and compared in global optimization process. It can be seen that general recommendations for optimization of separation in ion chromatography is application of chromatography exponential function criterion in combination with artificial neural networks retention model.

Izvorni jezik
Engleski

Znanstvena područja
Kemija

POVEZANOST RADA