TechnoRep - Repozitorijum Tehnološko-metalurškog fakulteta
Repozitorijum Tehnološko-metalurškog fakulteta
    • English
    • Српски
    • Српски (Serbia)
  • Srpski (latinica) 
    • Engleski
    • Srpski (ćirilica)
    • Srpski (latinica)
  • Prijava
Pregled zapisa 
  •   TechnoRep
  • Tehnološko-metalurški fakultet
  • Radovi istraživača / Researchers’ publications (TMF)
  • Pregled zapisa
  •   TechnoRep
  • Tehnološko-metalurški fakultet
  • Radovi istraživača / Researchers’ publications (TMF)
  • Pregled zapisa
JavaScript is disabled for your browser. Some features of this site may not work without it.

Optimization of artificial neural network for retention modeling in high-performance liquid chromatography

Samo za registrovane korisnike
2004
Autori
Vasiljević, Tatjana
Onjia, Antonije
Čokeša, Đuro
Laušević, Mila
article (publishedVersion)
Metapodaci
Prikaz svih podataka o dokumentu
Apstrakt
An artificial neural network (ANN) model for the prediction of retention times in high-performance liquid chromatography (HPLC) was developed and optimized. A three-layer feed-forward ANN has been used to model retention behavior of nine phenols as a function of mobile phase composition (methanol-acetic acid mobile phase). The number of hidden layer nodes, number of iteration steps and the number of experimental data points used for training set were optimized. By using a relatively small amount of experimental data (25 experimental data points in the training set), a very accurate prediction of the retention (percentage normalized differences between the predicted and the experimental data less than 0.6%) was obtained. It was shown that the prediction ability of ANN model linearly decreased with the reduction of number of experiments for the training data set. The results obtained demonstrate that ANN offers a straightforward way for retention modeling in isocratic HPLC separation of ...a complex mixture of compounds widely different in pK(a) and log K-ow values.

Ključne reči:
HPLC / phenols / experimental design / ANN / back-propagation
Izvor:
Talanta, 2004, 64, 3, 785-790
Izdavač:
  • Elsevier, Amsterdam

DOI: 10.1016/j.talanta.2004.03.032

ISSN: 0039-9140

PubMed: 18969673

WoS: 000224285300031

Scopus: 2-s2.0-4544266488
[ Google Scholar ]
URI
http://TechnoRep.tmf.bg.ac.rs/handle/123456789/702
Kolekcije
  • Radovi istraživača / Researchers’ publications (TMF)
Institucija/grupa
Tehnološko-metalurški fakultet

DSpace software copyright © 2002-2015  DuraSpace
O repozitorijumu TechnoRep | Pošaljite zapažanja

OpenAIRERCUB
 

 

Kompletan repozitorijumInstitucije/grupeAutoriNasloviTemeOva institucijaAutoriNasloviTeme

Statistika

Pregled statistika

DSpace software copyright © 2002-2015  DuraSpace
O repozitorijumu TechnoRep | Pošaljite zapažanja

OpenAIRERCUB