自动调节光谱响应的高精度多组分分析研究: 人工神经网络分光光度法

本文论证了人工神经网络(ANN)对多组分光度分析的应用。探讨了人工神经网络算法及其影响因素。用此法做五组分体系(维生素B1, B2, B6, C和菸酰胺)紫外光度分析, 并与CPA方法作比较。该方法的特点在于可由调节不同光谱范围的线性及非线性响应的计算过程来自动校正。研究结果证实了该方法的优越性。

A high precision method for accommodating spectral response automatically for multicomponent analysis: artificial neural networks spectrophotometry

This paper demonstrates the use of the artificial neural networks (ANN) for multicomponent spectrometric anal. The artificial neural networks algorithm, and its effect factors were investigated. Ultra-violet spectrophotometric anal. of a five-component system (vitamin B1, B2, B6, O, and niacinamide) is described and compared to the results from CPA method based on Beer's law (C. W. Brown, et al., 1982). The feature of the ANN approach is the anal. can be automatically adjusted by using the computing process to accommodate linear and nonlinear response in different spectral regions. The result of the study showed that the method is superior to some other popular methods.