摘要
本文将人工神经网络（ＡＮＮ）用于有机环境污染物紫外光谱库检索。对该神经网络的参数优化作了讨论。并用ＡＮＮ对噪声、杂质等因素的影响作了详细的考察。为了提高紫外光谱的分辨，本文提出用导数光谱作ＡＮＮ训练和检索，使网络的收敛速度明显加快，对检验光谱中杂质的容允程度明显增加。本文还将ＡＮＮ与传统的相关系数法作了比较。结果表明，ＡＮＮ法在抗噪声和杂质等方面明显优于相关系数法。
In this paper,the artificial neural network(ANN)was applied to the library search of UV spectra of organic environmental pollutants.The optimization of network parameters was discussed and the effects of noise and impurity were investigated in detail.The use of derivative spectra for ANN library search was proposed to enhance the resolution of the UV spectra.This method could speed up the convergence of the network and could enhance the tolerance of impurity level,but was subject to noise comparing with the ANN using conventional UV spectra.Results show that the ANN is superior to the correlation coefficient method in resistance to noise and impurity.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
1998年第6期680-686,共7页
Spectroscopy and Spectral Analysis
基金
国家教委优秀年轻教师基金
关键词
检索
ANN
环境污染物
有机污染物
紫外光谱库
Artificial neural network, Environmental pollutant, Ultraviolet spectra
