| 支有冉,宗若雯,王荣辉,李松阳.模式识别在火灾调查中的汽油分类问题的应用研究(英文)[J].火灾科学,2009,18(2):108-114. |
| 模式识别在火灾调查中的汽油分类问题的应用研究(英文) |
| The application of pattern recognition to the classification of regular gasoline in fire investigation |
| 投稿时间：2009-02-17 修订日期：2009-03-12 |
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| DOI：10.3969/j.issn.1004-5309.年.期.顺序 |
| 基金项目: |
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| 中文关键词: 助燃剂 主成分分析 KNN GC-MS 模式识别 |
| 英文关键词:Accelerant PCA KNN GC-MS Pattern recognition |
| 摘要点击次数: 513 |
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| 中文摘要: |
| 在火灾调查中,检测汽油成分并对其进行正确分类尤为重要。运用GC-MS对90#和93#两种普通汽油的共50个样本进行检测,所得的GC-MS原始数据通过PCA方法进行处理,以提取有用信息,避免冗余变量进入后续计算。在此基础上应用KNN方法对这两种汽油助燃剂进行分类。结果表明,KNN方法对这两种汽油的分类准确率达到100%,且当初始数据未经标准化预处理时也能达到同样准确的分类效果。研究表明:将模式识别方法正确地运用到助燃剂鉴定和分类工作中有助于火灾调查。 |
| 英文摘要: |
| Detection and accurate classification of gasoline is very important in fire investigation.In this paper,a total of 50 samples of regular gasoline,covering two different grades(90# and 93 #),were examined by gas chromatography-mass spectrometry(GC-MS).The GC-MS data were treated by Principal Component Analysis(PCA) to distill the information from the original dataset in order to avoid the redundant variables to be calculated.And k-nearest neighbors algorithm(KNN) was further applied to classify the two types of accelerant.The results showed that KNN could classify the two types of gasoline effectively,with the 100% probability(no prediction error),whether the data were normalized or not.The results indicated that the proper application of pattern recognition to the identification and classification of accelerant provided positive help in fire investigation. |
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