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基于K近邻算法的塑钢窗拉曼光谱分析

Raman Spectroscopy Analysis of Plastic Steel Window Based on K Nearest Neighbors Algorithm

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摘要

拉曼光谱技术在法庭科学中有着广泛的应用。采用显微激光拉曼光谱分析技术和K近邻算法对25个塑钢窗样本进行研究。通过主成分分析提取到5个主成分,并运用训练样本为测试样本的方法进行交互验证。当K=1时,测试样本的出错率最低,以区分贡献值最高的三个特征变量为参数建立分类模型,实现了对未知变量的准确归类,模型总分类准确率可达71%,区分效果良好,比直接通过谱图比较得到的结论更加准确。

Abstract

Raman spectroscopy has been used in forensic science widely. In this paper, laser Raman spectroscopy analysis technology and K nearest neighbors algorithm are used to study 25 plastic steel window samples. The five principal components are extracted by principal component analysis, and the experiment built interactive verification test with the method regarding the training sample as the test sample. When the K value equals to 1, the lowest training sample error rate appears. Taking the three highest contribution value characteristic variables as parameters to build the classification model to realize the accurate classification of the unknown variables, and the total correct rate is 71%. The above method is more accurate than the direct observation of the spectra.

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中图分类号:O657

DOI:10.3788/lop55.053001

所属栏目:光谱学

收稿日期:2017-10-10

修改稿日期:2017-11-25

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何欣龙:中国人民公安大学刑事科学技术学院, 北京 100038
陈利波:中国人民公安大学刑事科学技术学院, 北京 100038
王继芬:中国人民公安大学刑事科学技术学院, 北京 100038
桑国通:中国人民公安大学刑事科学技术学院, 北京 100038

联系人作者:王继芬(wangjifen58@126.com)

备注:何欣龙(1994—),男,硕士研究生,主要从事刑事技术方面的研究。 E-mail: 1078683050@qq.com

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引用该论文

He Xinlong,Chen Libo,Wang Jifen,Sang Guotong. Raman Spectroscopy Analysis of Plastic Steel Window Based on K Nearest Neighbors Algorithm[J]. Laser & Optoelectronics Progress, 2018, 55(5): 053001

何欣龙,陈利波,王继芬,桑国通. 基于K近邻算法的塑钢窗拉曼光谱分析[J]. 激光与光电子学进展, 2018, 55(5): 053001

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