| dc.creator |
Aktas, Ahmet Hakan |
|
| dc.creator |
PEKCAN, Guzide |
|
| dc.date |
2006-06-30T21:00:00Z |
|
| dc.date.accessioned |
2020-10-06T12:03:36Z |
|
| dc.date.available |
2020-10-06T12:03:36Z |
|
| dc.identifier |
fdd88b68-518d-41cc-9194-fd9de0cad983 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/fdd88b68-518d-41cc-9194-fd9de0cad983/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/77123 |
|
| dc.description |
The artificial neural network (ANN) trained by back-propagation learning was applied to process spectrophotometric data of mixed tartrazine, sunset yellow and allura red. By optimizing the network structure, accuracy was enhanced. The aim of this work is to propose the application of ANN methods to resolve mixtures of colorants in commercial products by using solid phase spectrophotometry. The proposed methods are rapid, easy to apply, inexpensive and suitable for analyzing the colorants in commercial products. The method takes advantage of sensitivity and selectivity. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Simultaneous spectrophotometric determination of tartrazine, sunset yellow and allura red in commercial products by artificial neural network calibration |
|
| dc.type |
info:eu-repo/semantics/article |
|