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Spectrophotometric Simultaneous Determination of Pyrocatechol, Resorcinol and Hydroquinone by LM-BP Neural Network

KAI Xiao-ming, SHEN Yu-hua, ZHANG Gu-xin, XIE An-jian Chemistry Department of Anqing Normal College, Anqing 246011, China College of Chemistry and Chemical Engineering, Anhui University, Hefei 230039, China  
By means of artificial neural network and Levenberg Marquardt Back Propagation (LM-BP) train algorithm, the three components of pyrocatechol, resorcinol and hydroquinone were determined simultaneously. The absorption spectra of these three components severely overlap in ultraviolet spectral range. Three wavelengths at 283.5, 279.5 and 276.5 run were selected for the determination. 25 mixture standard solutions were prepared according to orthogonal projection form L25 (56 ). Three kinds of components were trained. Mean Squared Error (MSE) reaching minimum value is 0.083 114 3. Meanwhile the contents of pyrocatechol, resorcinol and hydroquinone in six simulation mixture samples were predicted. The relative errors of the three kinds of components were slightly larger under the low concentration condition, and the mean relative error for most analytical results was less than 5 % , especialmy it is satisfactory for the analytical results of pyrocatechol and resorcinol with severely overlapped absorption spectra.
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