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Application of neural networks for response surface modeling in HPLC optimization

Authorized Users Only
1998
Authors
Agatonović-Kuštrin, Snežana
Zečević, Mira
Živanović, L
Tucker, I.G
Article (Published version)
Metadata
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Abstract
The usefulness of artificial neural networks for response surface modeling in HPLC optimization is compared with multiple regression methods. The results show that neural networks offer promising possibilities in HPLC method development. The predicted capacity factors of analytes were better to those obtained with multiple regression method.
Source:
Analytica Chimica Acta, 1998, 364, 1-3, 265-273
Publisher:
  • Elsevier Science BV, Amsterdam

DOI: 10.1016/S0003-2670(98)00121-4

ISSN: 0003-2670

WoS: 000074040300029

Scopus: 2-s2.0-0032565631
[ Google Scholar ]
71
59
URI
https://farfar.pharmacy.bg.ac.rs/handle/123456789/183
Collections
  • Radovi istraživača / Researchers’ publications
Institution/Community
Pharmacy
TY  - JOUR
AU  - Agatonović-Kuštrin, Snežana
AU  - Zečević, Mira
AU  - Živanović, L
AU  - Tucker, I.G
PY  - 1998
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/183
AB  - The usefulness of artificial neural networks for response surface modeling in HPLC optimization is compared with multiple regression methods. The results show that neural networks offer promising possibilities in HPLC method development. The predicted capacity factors of analytes were better to those obtained with multiple regression method.
PB  - Elsevier Science BV, Amsterdam
T2  - Analytica Chimica Acta
T1  - Application of neural networks for response surface modeling in HPLC optimization
VL  - 364
IS  - 1-3
SP  - 265
EP  - 273
DO  - 10.1016/S0003-2670(98)00121-4
ER  - 
@article{
author = "Agatonović-Kuštrin, Snežana and Zečević, Mira and Živanović, L and Tucker, I.G",
year = "1998",
abstract = "The usefulness of artificial neural networks for response surface modeling in HPLC optimization is compared with multiple regression methods. The results show that neural networks offer promising possibilities in HPLC method development. The predicted capacity factors of analytes were better to those obtained with multiple regression method.",
publisher = "Elsevier Science BV, Amsterdam",
journal = "Analytica Chimica Acta",
title = "Application of neural networks for response surface modeling in HPLC optimization",
volume = "364",
number = "1-3",
pages = "265-273",
doi = "10.1016/S0003-2670(98)00121-4"
}
Agatonović-Kuštrin, S., Zečević, M., Živanović, L.,& Tucker, I.G. (1998). Application of neural networks for response surface modeling in HPLC optimization. in Analytica Chimica Acta
Elsevier Science BV, Amsterdam., 364(1-3), 265-273.
https://doi.org/10.1016/S0003-2670(98)00121-4
Agatonović-Kuštrin S, Zečević M, Živanović L, Tucker I. Application of neural networks for response surface modeling in HPLC optimization. in Analytica Chimica Acta. 1998;364(1-3):265-273.
doi:10.1016/S0003-2670(98)00121-4 .
Agatonović-Kuštrin, Snežana, Zečević, Mira, Živanović, L, Tucker, I.G, "Application of neural networks for response surface modeling in HPLC optimization" in Analytica Chimica Acta, 364, no. 1-3 (1998):265-273,
https://doi.org/10.1016/S0003-2670(98)00121-4 . .

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