Naslov
Application of different artificial neural networks retention models for multi-criteria decision-making optimization in gradient ion chromatography

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

Izvornik
Separation science and technology (0149-6395) 45 (2010), 2; 236-243

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

Ključne riječi
ion chromatography ; artificial neural networks ; multi-criteria decision-making

Sažetak
In this work, the principles of multi-criteria decision-making were used to develop an efficient optimization strategy in gradient elution ion chromatographic analysis. Two different artificial neural network retention models (multi-layer perceptron and radial basis function), three different separation criterion functions (chromatography response function, separation factor product and normalized retention difference product) and four different robustness criterion functions (CR1-CR4) were examined. The shape of the calculated separation vs robustness response surface was used as principal criterion. Analysis time and minimum separation of adjacent peaks were additional criteria. The results showed that the radial basis artificial neural network retention model in combination with normalized retention difference product separation criterion function and CR3 robustness criterion function provided the optimal gradient ion chromatographic analysis.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Kemijsko inženjerstvo

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