Choosing between GC-FTIR and GC-MS spectra for an efficient intelligent identification of illicit amphetamines
Choosing between GC-FTIR and GC-MS spectra for an efficient intelligent identification of illicit amphetamines
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DOI：
10.1016/j.molstruc.2008.03.040
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发表时间：
2008-09-17
影响因子：
3.8
通讯作者：
Praisler, M.
中科院分区：
文献类型：
--
作者：
Gosav, S.;Dinica, R.;Praisler, M.
在本文中，我们对几个基于 GC-MR 和 GC-MS 谱图鉴定非法安非他明的专家系统进行了比较分析。该系统是使用人工神经网络（ANN）构建的，专门用于识别安非他明。结构-活性关系被纳入知识库，使系统能够根据毒理学活性（兴奋剂或致幻剂）识别安非他明。结果表明，GC-FTIR 数据与专家系统的效率更为相关，这可能是因为这些光谱构成了分子结构的“指纹”。我们还提出了光谱分析，以评估未知样品识别所基于的每种类型输入变量（吸光度和丰度）的相关性。 (C) 2008 Elsevier B.V. 保留所有权利。
In this paper we are presenting a comparative analysis between several expert systems built for the identification of illicit amphetamines based on their GC-MR and GC-MS spectra. The systems were built using Artificial Neural Networks (ANNs), and are dedicated to the recognition of amphetamines. Structure-activity relationships are incorporated into the knowledge base, allowing the systems to identify the amphetamines according to their toxicological activity (stimulant or hallucinogenic). The results show that GC-FTIR data are much more relevant for the efficiency of the expert systems, probably due to the fact that these spectra constitute a "fingerprint" of the molecular structures. We are also presenting a spectroscopic analysis in order to evaluate the relevance of each type of input variable (absorption and abundance) on which the recognition of an unknown sample is based. (C) 2008 Elsevier B.V. All rights reserved.