Ultra-Wideband (UWB) characteristic estimation of elliptic patch antenna based on machine learning techniques

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dc.contributor.authorGencoglan, Duygu Nazan
dc.contributor.authorArslan, Mustafa Turan
dc.contributor.authorColak, Sule
dc.contributor.authorYildirim, Esen
dc.date.accessioned2024-09-18T19:54:25Z
dc.date.available2024-09-18T19:54:25Z
dc.date.issued2020
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractIn this study, estimation of Ultra-Wideband (UWB) characteristics of microstrip elliptic patch antenna is investigated by means of k-nearest neighborhood algorithm. A total of 16,940 antennas are simulated by changing antenna dimensions and substrate material. Antennas are examined by observing Return Loss and Voltage Standing Wave Ratio (VSWR) characteristics. In the study, classification of antennas in terms of having UWB characteristics results in accuracies higher than 97%. Additionally, Consistency based Feature Selection method is applied to eliminate redundant and irrelevant features. This method yields that substrate material does not affect the UWB characteristics of the antenna. Classification process is repeated for the reduced feature set, reaching to 97.44% accuracy rate. This result is validated by 854 antennas, which are not included in the original antenna set. Antennas are designed for seven different substrate materials keeping all other parameters constant. Computer Simulation Technology Microwave Studio (CST MWS) is used for the design and simulation of the antennas.en_US
dc.identifier.doi10.1515/freq-2019-0210
dc.identifier.endpage358en_US
dc.identifier.issn0016-1136
dc.identifier.issn2191-6349
dc.identifier.issue9-10en_US
dc.identifier.scopus2-s2.0-85087962760en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage351en_US
dc.identifier.urihttps://doi.org/10.1515/freq-2019-0210
dc.identifier.urihttps://hdl.handle.net/20.500.12483/7730
dc.identifier.volume74en_US
dc.identifier.wosWOS:000575409400007en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWalter De Gruyter Gmbhen_US
dc.relation.ispartofFrequenzen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectantenna designen_US
dc.subjectconsistency based feature selection (CbFS)en_US
dc.subjectk-Nearest neighborhood algorithm (kNN)en_US
dc.subjectmicrostrip patch antennaen_US
dc.subjectsubstrate materialsen_US
dc.subjectUWB antennaen_US
dc.titleUltra-Wideband (UWB) characteristic estimation of elliptic patch antenna based on machine learning techniquesen_US
dc.typeArticleen_US

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