| 人工神经网络法测定五组分红外光谱体系 |
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| 引用本文： | 李燕,孙秀云,王俊德.人工神经网络法测定五组分红外光谱体系[J].光谱学与光谱分析,2000,20(6):773-776. |
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| 作者姓名： | 李燕 孙秀云 王俊德 |
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| 作者单位： | 南京理工大学现代光谱研究室,南京,210014 |
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| 基金项目： | 国家自然科学基金，国家教委博士点基金，江苏省科学技术委员会的资助项目 |
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| 摘 要： | 介绍了人工神经网络在非线性多组分校准中的应用，所用三层神经网络由反向传播算法来训练。采用大量模拟数据训练神经网络，得到了一系列优化参数，选择红外谱图严重重叠的五种大气有机毒物作为多组分体系，相对标准误差（ＲＳＤ％）、百分标准预测误差（ＳＥＰ％）和百分标准误差（ＳＥＣ％）被用于衡量神经网络的性能。
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| 关 键 词： | 多组分分析 有机分析 红外光谱 人工神经网络 |
Determination of Five Compounent Infrared Spectra System with Artificial Neural Network |
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| Yan LI,Xiuyun SUN,Junde WANG.Determination of Five Compounent Infrared Spectra System with Artificial Neural Network[J].Spectroscopy and Spectral Analysis,2000,20(6):773-776. |
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| Authors: | Yan LI Xiuyun SUN Junde WANG |
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| Institution: | Laboratory of Advanced Spectroscopy, Nanjing University of Science and Technology, 210014 Nanjing. |
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| Abstract: | This article demonstrates the application of artficial neural network in multi component analysis.Parameters were obtained after the BP network was trained with large amount of simulated data.Five organic toxins whose FTIR spectra are strongly overlapped were used to make the multi component system.The relative standard deviation(RSD%),the percent standard error of prediction samples(SEP%) and the percent standard error of calibration samples(SEC%) were used for evaluating the ability of the neural network. |
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| Keywords: | Multi component analysis Organic compound analysis FTIR Artificial neural network |
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