|
|||||
|
|
| 人工神经网络对VOCs的自动识别 | |
| 引用本文： | 刘丙萍,李燕,张琳,张黎明,王晓斐,王俊德.人工神经网络对VOCs的自动识别[J].光谱学与光谱分析,2006,26(1):51-53. |
| 作者姓名： | 刘丙萍 李燕 张琳 张黎明 王晓斐 王俊德 |
| 作者单位： | 1. 南京理工大学现代光谱研究室,江苏,南京,210014;曲阜师范大学化学科学学院,山东,曲阜,273165 2. 南京理工大学现代光谱研究室,江苏,南京,210014 3. 南京理工大学现代光谱研究室,江苏,南京,210014;南京大学化工学院,江苏,南京,210093 |
| 基金项目： | 中国科学院资助项目 , 中国博士后科学基金 , 南京理工大学校科研和教改项目 |
| 摘 要： | 利用人工神经网络(ANN)对严重混叠的傅里叶变换红外光谱图进行了定性和定量解析.通过大量模拟数据训练神经网络后,引用了新的评价标准--逼近度来选择最优网络模型.利用此优化网络对两类光谱图进行了解析,考察了网络的泛化能力.结果表明:该网络不仅能够对两组分同时存在时的样本进行准确解析,而且对于未知单组分光谱图,也能够进行准确鉴别和定量分析.可见,该研究为人工神经网络在单组分和多组分未知物的定性和定量分析方面提供了一种新思路. |
| 关 键 词： | 傅里叶变换红外光谱 人工神经网络 多组分分析 未知物鉴定 |
| 文章编号： | 1000-0593（2006）01-0051-03 |
| 收稿时间： | 2004-09-16 |
| 修稿时间： | 2005-01-31 |
Automated Recognition of VOCs Using Artificial Neural Networks |
|
| LIU Bing-ping,LI Yan,ZHANG Lin,ZHANG Li-ming,WANG Xiao-fei,WANG Jun-de.Automated Recognition of VOCs Using Artificial Neural Networks[J].Spectroscopy and Spectral Analysis,2006,26(1):51-53. | |
| Authors: | LIU Bing-ping LI Yan ZHANG Lin ZHANG Li-ming WANG Xiao-fei WANG Jun-de |
| Institution: | 1. Laboratory of Advanced Spectroscopy, Nanjing University of Science and Technology, Nanjing 210014, China; 2. Department of Chemistry, Qufu Normal University, Qufu 273165, China; 3. Department of Chemistry, Nanjing University, Nanjing 210093, China |
| Abstract: | Quantitative analysis of FTIR spectra, which are seriously overlapped in the spectral bands, was studied by artificial neural networks. The optimum network was chosen by a new criterion, i.e. the degree of approximation. After the network was established, two kinds of spectra were re.solved. It was demonstrated that accurate results could be obtained when two components were both included. In addition, the unknown spectrum could be identified and quantified. It was showed that the artificial neural network has excellent non-linear ability of solution. Meanwhile, the method provides an efficient approach to the identification and quantification of the unknown samples. |
| Keywords: | FTIR Artificial neural network Multi-component analysis Identification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |