The application of artificial neural network(ANN) and near-infrared spectroscopy for pharmaceutical nondestructive quantitative analysis of Paracetamol was investigated. The artificial neural network patterns of Paracetamol tablet medicines, powder medicines, first derivative spectra and second derivative spectra were established, and they were compared each other. The uncertain specimens were predicted. The parameters affecting ANN were discussed. A new network evaluation criterion, i.e., the degree of approximation, was employed, and the predicted results were reliable.
The application of artificial neural network for pharmaceutical nondestructive quantitative analysis was investigated. The real data set from near infrared reflectance spectra of trimethoprim powder pharmaceutical were used to built up artificial network to predict unknown samples. The factors affecting network were discussed. A new network evaluation criterion, the degree of approximation, was employed. Owing to good nonlinear multivariate calibration nature of ANN, the predicted result was reliable. [WT5HZ]
