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Detection of Hazardous Liquids Using Microwave Data and Well-Known Classification Algorithms
Russian Journal of Nondestructive Testing ( IF 0.9 ) Pub Date : 2020-11-23 , DOI: 10.1134/s106183092009003x
Ebru Efeoglu , Gurkan Tuna

Abstract

The recent increase in terrorist attacks realized using liquid explosives has made it important to develop quick and reliable methods that can distinguish between nonhazardous liquids and other liquids that can be used in these explosives. Since the stability and sensitivity properties of microwave systems are high, microwave frequency band is preferred to differentiate hazardous liquids from non-hazardous liquids. In this study, a noncontact system based on electromagnetic response measurements of liquids in microwave frequency band is proposed to develop a classification approach that can be used in liquid scanners. Naive Bayes, linear discriminant analysis, qualitative data analysis, support vector machine, sequential minimal optimization, K-nearest neighbors classification algorithms are used to classify liquids and their classification performances are analyzed. The results of the set of classification experiments prove the success of the proposed measurement method. As the results prove, K-nearest neighbors is the most appropriate classification algorithm for hazardous liquid detection. Since it can be easily implemented and its detection process is fast, a classification system based on the proposed approach can be very useful in airports and shopping malls.



中文翻译:

使用微波数据和知名分类算法检测有害液体

摘要

最近使用液体炸药实现的恐怖袭击有所增加,因此重要的是开发一种快速可靠的方法,以区分无害液体和可用于这些炸药的其他液体。由于微波系统的稳定性和灵敏度高,因此最好使用微波频段来区分危险液体和非危险液体。在这项研究中,提出了一种基于微波频带内液体电磁响应测量的非接触式系统,以开发一种可用于液体扫描仪的分类方法。朴素贝叶斯,线性判别分析,定性数据分析,支持向量机,顺序最小优化,K采用近邻分类算法对液体进行分类,并对分类性能进行了分析。一组分类实验的结果证明了所提出的测量方法的成功。结果证明,K近邻法是危险液体检测最合适的分类算法。由于它易于实现且检测过程很快,因此基于该方法的分类系统在机场和购物中心中非常有用。

更新日期:2020-11-25
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