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https://open.uns.ac.rs/handle/123456789/30208| Title: | Nonlinear modelling of HPLC retention of a series of pesticides using neural networks with Broyden-Fletcher-Goldfarb-Shanno algorithm | Authors: | Kovačević, Strahinja Gadžurić, Slobodan Jevrić, Lidija Podunavac-Kuzmanović, Sanja Vraneš, Milan |
Issue Date: | 2014 | Publisher: | Belgrade: Society of Physical Chemists of Serbia | Journal: | Proceedings, 12th International Conference on Fundamental and Applied Aspects of Physical Chemistry – PHYSICAL CHEMISTRY 2014, Belgrade, Serbia, 2014, Volume III | Conference: | 12th International Conference on Fundamental and Applied Aspects of Physical Chemistry – PHYSICAL CHEMISTRY 2014, Belgrade, Serbia, 2014, 22.09.–26.09., No 12 | Abstract: | The main aim of this study was to establish the artificial neural networks (ANNs) with the ability to precisely predict the reversed-phase HPLC retention time of a set of 77 pesticides extracted from groundwater based on in silico molecular descriptors. After training of 1000 ANNs applying Broyden-Fletcher-Goldfarb-Shanno training algorithm, three of them were selected as the best. The statistical and validation parameters of these networks indicate their outstanding prediction ability. | URI: | https://open.uns.ac.rs/handle/123456789/30208 | ISBN: | 9788682475323 | DOI: | (BISIS)90590 (BISIS)90590 (BISIS)90590 (BISIS)90590 |
| Appears in Collections: | TF Publikacije/Publications |
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