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dc.contributor.authorÖzdemir, Durmuş
dc.contributor.authorDinç, Erdal
dc.contributor.authorBaleanu, Dimutru
dc.date.accessioned2017-12-04T07:23:32Z
dc.date.available2017-12-04T07:23:32Z
dc.date.issued2010-02
dc.identifier.citationÖzdemir, D., Dinç, E., and Baleanu, D. (2010). UV-Visible spectrophotometric quantitative analysis of ternary mixture Using multivariate calibration methods optimized by a genetic algorithm. Revista de Chimie, 61(2), 146-153.en_US
dc.identifier.issn0034-7752
dc.identifier.urihttp://hdl.handle.net/11147/6530
dc.description.abstractSimultaneous determination of ternary mixtures of caffeine, paracetamol and metamizol in commercial tablet formulations using UV-visible spectrophotometry combined with classical least squares (CLS) and genetic algorithm (GA) based multivariate calibration methods were demonstrated. The three genetic multivariate calibration methods are named as Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The GR method is based on a genetic algorithm based wavelength selection followed by a simple linear regression step whereas the GCLS and GILS are multivariate calibration methods modified by a wavelength selection principle using a genetic algorithm. The sample data set contains the UV-visible spectra of 47 synthetic mixtueres (4 to 48 μg/mL) and 16 tablets containing these components from two different producers. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the three components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of 0.04 and 2.34 μg/mL for all the four methods. Predictive ability of the calibration models generated with synthetic samples was tested with actual tablet samples and results obtained from four methods were compared. The SEP values for the tablets were in the range of 0.31 and 15.44 mg/tablets.en_US
dc.language.isoengen_US
dc.publisherCentral de Documentare Al Industriei Chimice Rien_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMultivariate calibrationen_US
dc.subjectUV-visible spectrophotometryen_US
dc.titleUV-Visible spectrophotometric quantitative analysis of ternary mixture Using multivariate calibration methods optimized by a genetic algorithmen_US
dc.typearticleen_US
dc.contributor.authorIDTR115516en_US
dc.contributor.institutionauthorÖzdemir, Durmuş
dc.relation.journalRevista de Chimieen_US
dc.contributor.departmentİYTE, Fen Fakültesi, Kimya Bölümüen_US
dc.identifier.volume61en_US
dc.identifier.issue2en_US
dc.identifier.startpage146en_US
dc.identifier.endpage153en_US
dc.identifier.wosWOS:000276216200009
dc.identifier.scopusSCOPUS:2-s2.0-77950798334
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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