Application of neural networks for response surface modeling in HPLC optimization

dc.creator	Agatonović-Kuštrin, Snežana
dc.creator	Zečević, Mira
dc.creator	Živanović, L
dc.creator	Tucker, I.G
dc.date.accessioned	2019-09-02T10:50:34Z
dc.date.available	2019-09-02T10:50:34Z
dc.date.issued	1998
dc.identifier.issn	0003-2670
dc.identifier.uri	https://farfar.pharmacy.bg.ac.rs/handle/123456789/183
dc.description.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.	en
dc.publisher	Elsevier Science BV, Amsterdam
dc.rights	restrictedAccess
dc.source	Analytica Chimica Acta
dc.title	Application of neural networks for response surface modeling in HPLC optimization	en
dc.type	article
dc.rights.license	ARR
dcterms.abstract	Живановић, Л; Aгатоновић-Куштрин, Снежана; Зечевић, Мира; Туцкер, И.Г;
dc.citation.volume	364
dc.citation.issue	1-3
dc.citation.spage	265
dc.citation.epage	273
dc.citation.other	364(1-3): 265-273
dc.citation.rank	M21
dc.identifier.wos	000074040300029
dc.identifier.doi	10.1016/S0003-2670(98)00121-4
dc.identifier.scopus	2-s2.0-0032565631
dc.type.version	publishedVersion