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Genetic Algorithm Based Potential Selection in Simultaneous Voltammetric Determination of Isoniazid and Hydrazine by Using Partial Least Squares (PLS) and Artificial Neural Networks (ANNs)
Author(s) -
Majidi Mir Reza,
Jouyban Abolghasem,
AsadpourZeynali Karim
Publication year - 2005
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.200403204
Subject(s) - hydrazine (antidepressant) , isoniazid , partial least squares regression , genetic algorithm , artificial neural network , voltammetry , chemistry , materials science , selection (genetic algorithm) , algorithm , electrode , electrochemistry , computer science , chromatography , mathematics , artificial intelligence , mathematical optimization , machine learning , medicine , tuberculosis , pathology
The voltammetric behavior of isoniazid and hydrazine at an overoxidized polypyrrole modified glassy carbon electrode has been investigated. The obtained cyclic voltammograms showed that their oxidation peaks were overlapped and it is difficult to determine them individually from a mixture without separation. To overcome this limitation, a procedure was proposed for resolution of overlapped voltammetric signals from mixtures of isoniazid and hydrazine. In this procedure, genetic algorithm was used for the selection of potentials for partial least squares. A feed forward artificial neural network with back propagation error algorithm was used to process the nonlinear relationship between currents and concentrations of hydrazine and isoniazid. The proposed method was suitable for determination of isoniazid in pharmaceutical tablets and detection of hydrazine impurities in the same samples.