Pregled bibliografske jedinice broj: 506453
Use of Genetic Algorithms and Artificial Neural Networks to Predict the Resolution of Aminoacids in Thin-Layer Chromatography
Use of Genetic Algorithms and Artificial Neural Networks to Predict the Resolution of Aminoacids in Thin-Layer Chromatography // JPC. Journal of planar chromatography, modern TLC, 24 (2011), 1; 16-22 doi:10.1556/JPC.24.2011.1.3 (međunarodna recenzija, članak, znanstveni)
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Naslov
Use of Genetic Algorithms and Artificial Neural Networks to Predict the Resolution of Aminoacids in Thin-Layer Chromatography
Autori
Rolich, Tomislav ; Rezić, Iva
Izvornik
JPC. Journal of planar chromatography, modern TLC (0933-4173) 24
(2011), 1;
16-22
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Thin layer chromatography ; Optimization ; Artificial neural networks ; Genetic algorithms
Sažetak
A novel method is proposed for optimization of simultaneous thin layer chromatographic separation of seven amino acids. For this purpose we used a useful combination of genetic algorithms (GA) with artificial neural networks (ANN). Methods investigated in this work were successfully used for prediction of resolution factor (RS) and optimization of thin layer chromatographic separation of model solutions containing seven compounds. Very good correlation was achieved between predicted and calculated RS data, and low absolute and relative errors were obtained.
Izvorni jezik
Engleski
Znanstvena područja
Kemija, Kemijsko inženjerstvo, Računarstvo
POVEZANOST RADA
Projekti:
117-0000000-3254 - Evolucijski algoritmi za optimiranje elektromagnetskog opterećenja okoliša (Grundler, Darko, MZOS ) ( CroRIS)
Ustanove:
Tekstilno-tehnološki fakultet, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
