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首页> 外文会议>International Conference on Computational Science and Its Applications(ICCSA 2006) pt.1; 20060508-11; Glasgow(GB) >Rapid Determination of Compound Rifampicin Tablets Using Near Infrared Spectroscopy with Artificial Neural Network
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Rapid Determination of Compound Rifampicin Tablets Using Near Infrared Spectroscopy with Artificial Neural Network

机译：人工神经网络近红外光谱法快速测定复方利福平片

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摘要

This paper has investigated the application of near infrared (NIR) spectroscopy with artificial neural network (ANN) for synchronous and rapid determination of rifampicin, isoniazid and pyrazinamide in compound rifampicin tablets. We have developed Back-Propagation (BP) Networks which adopted Levenberg-Marquardt training algorithm and Log-sigmoid transfer function basing on NIR spectra of samples and contents of rifampicin, isoniazid and pyrazinamide. The degree of approximation, a new evaluation criterion of the network was employed, which proved the accuracy of the predicted results. The BP Networks have been optimized by selecting suitable topologic structure parameters and the best numbers of training. Using these BP Networks for predicting the amounts of rifampicin, isoniazid and pyrazinamide in prediction set, the root mean square error of prediction (RMSEP) are 0.00668, 0.00508 and 0.00680. These results demonstrate that this method is feasible. This method is convenient, rapid, has no pretreatment and no pollution.
机译：本文研究了人工神经网络（ANN）在近红外（NIR）光谱中用于同步快速测定复方利福平片中的利福平，异烟肼和吡嗪酰胺的应用。我们已经开发了基于样本的近红外光谱以及利福平，异烟肼和吡嗪酰胺含量的Levenberg-Marquardt训练算法和Log-Sigmoid传递函数的反向传播（BP）网络。逼近度是网络的一种新的评价标准，证明了预测结果的准确性。通过选择合适的拓扑结构参数和最佳训练次数，对BP网络进行了优化。使用这些BP网络预测预测集中的利福平，异烟肼和吡嗪酰胺的量，预测的均方根误差（RMSEP）为0.00668、0.00508和0.00680。这些结果表明该方法是可行的。该方法方便，快捷，无需预处理，无污染。

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