使用气相色谱/质谱数据通过投影差分分辨映射和模糊规则建立专家系统分类进行易燃液体鉴定。

Ignitable liquid identification using gas chromatography/mass spectrometry data by projected difference resolution mapping and fuzzy rule-building expert system classification.

机构信息

Center for Intelligent Chemical Instrumentation, Clippinger Laboratories, Department of Chemistry and Biochemistry, OHIO University, Athens, OH 45701-2979, USA.

出版信息

Forensic Sci Int. 2012 Jul 10;220(1-3):210-8. doi: 10.1016/j.forsciint.2012.03.003. Epub 2012 Apr 1.

DOI:10.1016/j.forsciint.2012.03.003

PMID:22472078

Abstract

The gasoline and kerosene collected from different locations in the United States were identified by gas chromatography/mass spectrometry (GC/MS) followed by chemometric analysis. Classifications based on two-way profiles and target component ratios were compared. The projected difference resolution (PDR) mapping was applied to measure the differences among the ignitable liquid (IL) samples by their GC/MS profiles quantitatively. Fuzzy rule-building expert systems (FuRESs) were applied to classify individual ILs. The FuRES models yielded correct classification rates greater than 90% for discriminating between samples. PDR mapping, a new method for characterizing complex data sets was consistent with the FuRES classification result.

摘要

从美国不同地点收集的汽油和煤油通过气相色谱/质谱法（GC/MS）进行鉴定，然后进行化学计量分析。基于双向谱和目标成分比的分类进行了比较。应用投影差异分辨率（PDR）映射定量测量 GC/MS 谱图中不同易燃液体（IL）样品之间的差异。模糊规则生成专家系统（FuRES）用于对个别 IL 进行分类。FuRES 模型对区分样品的正确分类率大于 90%。用于描述复杂数据集的新方法 PDR 映射与 FuRES 分类结果一致。