Use of Hybrid Clustering and Scattering Parameters for Liquid Classification

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dc.contributor.authorEfeoglu, Ebru
dc.contributor.authorTuna, Gurkan
dc.date.accessioned2024-06-12T10:50:18Z
dc.date.available2024-06-12T10:50:18Z
dc.date.issued2022
dc.departmentTrakya Üniversitesien_US
dc.description.abstractWith the advancement of technology, the use of machine learning techniques has increased. The need for the prevention of terrorist attacks has brought upon the use of machine learning techniques to explosive detection. Flammable liquids such as alcohol are easily available and widely used in various terrorist attacks. In this study, a new microwave measurement system is developed and a hybrid clustering approach is proposed to classify liquids. With the proposed measurement system, the reflection coefficient (S-11 parameter) of liquids in bottles is measured at room temperature and these measurements are used as inputs by the proposed clustering algorithm. The results obtained using the proposed clustering algorithm are compared with the results obtained using a set of well-known clustering algorithms, that is, K-means, hierarchical clustering, farthest first, and fuzzy C-means, in order to make a fair comparison. The results show that the proposed clustering algorithm provides 100% accuracy and is superior to the well-known algorithms used in this study. The results will enable us to manufacture a low-cost liquid scanner for railway stations and shopping malls as well as small airports. The proposed liquid scanner's design was completed, and the manufacturing phase has been started.en_US
dc.identifier.doi10.54614/electrica.2022.21160
dc.identifier.endpage243en_US
dc.identifier.issn2619-9831
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85132967792en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage237en_US
dc.identifier.trdizinid529360en_US
dc.identifier.urihttps://doi.org/10.54614/electrica.2022.21160
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/529360
dc.identifier.urihttps://hdl.handle.net/20.500.14551/17961
dc.identifier.volume22en_US
dc.identifier.wosWOS:000834655200011en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.publisherIstanbul Univ-Cerrahpasaen_US
dc.relation.ispartofElectricaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAccuracyen_US
dc.subjectExplosive Liquidsen_US
dc.subjectFlammable Liquidsen_US
dc.subjectHybrid Clustering Algorithmen_US
dc.subjectLiquid Classificationen_US
dc.subjectGasolineen_US
dc.subjectSpectroscopyen_US
dc.titleUse of Hybrid Clustering and Scattering Parameters for Liquid Classificationen_US
dc.typeArticleen_US

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