Artificial neural network for simultaneous determination of two components of compound paracetamol and diphenhydramine hydrochloride powder on NIR spectroscopy |
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Authors: | Ying Dou Yuqiu Ren |
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Affiliation: | a College of Chemistry, Department of Chemistry, Jilin University, 119 Jiefang Road, Changchun, Jilin 130021, PR China b Department of Pharmacy, Changchun Medical College, Changchun 130031, PR China c Baicheng Medical College, Baicheng 137000, PR China |
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Abstract: | Diffuse reflectance near-infrared (NIR) spectroscopy is a technique widely used for rapid and non-destructive analysis of solid samples. A method for simultaneous analysis of the two components of compound paracetamol and diphenhydramine hydrochloride powdered drug has been developed by using artificial neural network (ANN) on near-infrared (NIR) spectroscopy. An ANN containing three layers of nodes was trained. Various ANN models based on pretreated spectra (first-derivative, second-derivative and standard normal variate; SNV) were tested and compared, respectively. In the models the concentration of paracetamol and caffeine as active principles of compound paracetamol and diphenhydramine hydrochloride powder was determined simultaneously. Partial least squares regression (PLS) multivariate calibrations were also used, which were compared with ANN. The best model was obtained at first-derivative spectra. We have also discussed the parameters that affected the networks and predicted the test set (unknown) specimens. The degree of approximation, a new evaluation criteria of the network were employed, which proved the accuracy of the predicted results. |
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Keywords: | Artificial neural networks NIR spectroscopy Degree of approximation Compound paracetamol and diphenhydramine hydrochloride powder |
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