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[人工神经网络在苯酚和间苯二酚同步荧光光谱测定中的应用]

[Application of artificial neural network to simultaneous spectro-fluorimetric determination of phenol and resorcinol].

作者信息

Wu Gen-hua, He Chi-yang, Chen Rong

机构信息

Department of Chemistry, Anqing Normal College, Anqing 246001, China.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2002 Oct;22(5):813-5.

Abstract

By the means of artificial neural network and Levenberg-Marquardt back-propagation train algorithm, the two components of phenol, resorcinol were determined simultaneously, in which the fluorescence spectra overlapped. In 290-345 nm, the fluorescence intensity at 14 wavelengths were taken as character of artificial neural network, and samples were arranged by method of equality design. The mean recovery of phenol and resorcinol were 100.2%, 99.99% respectively. The RSD of the results were 0.4% and 1.3%.

摘要

采用人工神经网络和Levenberg-Marquardt反向传播训练算法,对荧光光谱重叠的苯酚和间苯二酚两组分进行了同时测定。在290~345nm范围内,选取14个波长处的荧光强度作为人工神经网络的特征量,并采用均匀设计法安排样本。苯酚和间苯二酚的平均回收率分别为100.2%和99.99%。结果的相对标准偏差分别为0.4%和1.3%。

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