Document Detail

Application of principal component-artificial neural network models for simultaneous determination of phenolic compounds by a kinetic spectrophotometric method.
MedLine Citation:
PMID:  18272286     Owner:  NLM     Status:  MEDLINE    
A multicomponent analysis method based on principal component analysis-artificial neural network models (PC-ANN) is proposed for the determination of phenolic compounds. The method relies on the oxidative coupling of phenols (phenol, 2 chlorophenol, 3-chlorophenol and 4-chlorophenol) to N,N-diethyl-p-phenylenediamine in the presence of hexacyanoferrate(III). The reaction monitored at analytical wavelength 680 nm of the dye formed. Phenols can be determined individually over the concentration range 0.1-7.0 microg ml(-1). Differences in the kinetic behavior of the four species were exploited by using PC-ANN, to resolve mixtures of phenol. After reducing the number of kinetic data using principal component analysis, an artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. The optimized ANN allows the simultaneous quantitation of four analytes in mixtures with relative standard errors of prediction in the region of 5% for four species. The results show that PC-ANN is an efficient method for prediction of the four analytes.
Masoumeh Hasani; Mahsa Moloudi
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Publication Detail:
Type:  Journal Article     Date:  2008-01-04
Journal Detail:
Title:  Journal of hazardous materials     Volume:  157     ISSN:  0304-3894     ISO Abbreviation:  J. Hazard. Mater.     Publication Date:  2008 Aug 
Date Detail:
Created Date:  2008-06-23     Completed Date:  2008-10-06     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9422688     Medline TA:  J Hazard Mater     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  161-9     Citation Subset:  IM    
Faculty of chemistry, Bu-Ali Sina University, Hamedan 65174, Iran.
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MeSH Terms
Environmental Pollutants / analysis*
Ferricyanides / chemistry
Hydrogen-Ion Concentration
Neural Networks (Computer)*
Phenols / analysis*
Phenylenediamines / chemistry
Principal Component Analysis*
Sensitivity and Specificity
Spectrophotometry, Ultraviolet
Reg. No./Substance:
0/Environmental Pollutants; 0/Ferricyanides; 0/Phenols; 0/Phenylenediamines; 13746-66-2/potassium ferricyanide; 93-05-0/N,N-diethyl 4-phenylenediamine

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