Ultra-Wideband (UWB) characteristic estimation of elliptic patch antenna based on machine learning techniques
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Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Walter De Gruyter Gmbh
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In 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.
Açıklama
Anahtar Kelimeler
antenna design, consistency based feature selection (CbFS), k-Nearest neighborhood algorithm (kNN), microstrip patch antenna, substrate materials, UWB antenna
Kaynak
Frequenz
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
74
Sayı
9-10
