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Elman回归神经网络研究同时定量分析紫外重叠光谱
引用本文:高玲,任守信. Elman回归神经网络研究同时定量分析紫外重叠光谱[J]. 石油化工, 2004, 33(3): 266-269
作者姓名:高玲  任守信
作者单位:内蒙古大学,化学化工学院,内蒙古,呼和浩特,010021
基金项目:国家自然科学基金项目(29965001),内蒙古自然科学基金项目(2002208020115)。
摘    要:应用Elman回归神经网络对同时定量分析紫外重叠光谱进行了研究。还应用偏最小二乘法作为对比,编制了PERNN和PPLS程序执行有关计算。通过最佳化确定了Elman回归网络的结构和参数。3种组分(α-萘胺、对硝基苯胺、联苯胺)经Elman回归神经网络定量测定表明,该方法是成功的,且优于偏最小二乘法。

关 键 词:Elman回归神经网络  同时定量分析  紫外重叠光谱  偏最小二乘法
文章编号:1000-8144(2004)03-0266-04
修稿时间:2003-09-16

Study of Simultaneous Quantitative Analysis of Overlapping UV Spectra by Elman Recurrent Neural Network
Gao Ling,Ren Shouxin. Study of Simultaneous Quantitative Analysis of Overlapping UV Spectra by Elman Recurrent Neural Network[J]. Petrochemical Technology, 2004, 33(3): 266-269
Authors:Gao Ling  Ren Shouxin
Abstract:Elman recurrent neural network(Elman RNN)was applied to study the simultaneous quantitative analysis of overlapping UV spectra.The partial least squares(PLS)method was also applied in this study for comparison.Two programs(PERNN and PPLS)were designed to perform the calculations.Through optimization the structure and parameters of Elman recurrent neural network were defined.Three components(α-naphthylamine,p-nitroamine and benzide)were determined quantitatively by Elman RNN.Experimental results showed the method to be successful and better than PLS.
Keywords:Elman recurrent neural network  simultaneous quantitative analysis  overlapping UV spectra  partial least squares  
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