Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı

Semih Pak; M. Tahir Güneşer; Cihat Şeker

doi:10.1109/SIU61531.2024.10601083

Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı

Semih Pak
, M. Tahir Güneşer
, Cihat Şeker

Karabuk University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

Özet

Developments in artificial intelligence directly affect various fields of science. This is especially important in the solution of higher-order models and systems that do not have an exact equation. Due to the difficulties in modeling electromagnetic systems, artificial intelligence-based studies have a special importance in this field. In this study, the multidimensional optimization of a compact microstrip monopole antenna that can be used in next generation communication applications is studied with a new artificial intelligence algorithm, the red fox algorithm. Thus, a compact microstrip antenna with broadband (8.75 GHz - 11.25 GHz) radiation at 10 GHz resonant frequency is designed for X-Band applications.

Tercüme edilen katkı başlığı	Optimization of Compact Microstrip Monopole Antenna Parameters with NS-RFO and Artificial Intelligence in Antenna Design
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9798350388961
DOI'lar	https://doi.org/10.1109/SIU61531.2024.10601083
Yayın durumu	Yayınlandı - 2024
Harici olarak yayınlandı	Evet
Etkinlik	32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Mersin, Turkey Süre: 15 May 2024 → 18 May 2024

Yayın serisi

Adı	32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024
Ülke/Bölge	Turkey
Şehir	Mersin
Periyot	15/05/24 → 18/05/24

Bibliyografik not

Publisher Copyright:
© 2024 IEEE.

Keywords

5G
6G
RFO
optimization
pareto

Belgeye Erişim

10.1109/SIU61531.2024.10601083

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Pak, S., Güneşer, M. T., & Şeker, C. (2024). Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı. In 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings (32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU61531.2024.10601083

Pak, Semih ; Güneşer, M. Tahir ; Şeker, Cihat. / Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı. 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2024. (32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings).

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title = "Kompakt Mikro{\c s}erit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı",

abstract = "Developments in artificial intelligence directly affect various fields of science. This is especially important in the solution of higher-order models and systems that do not have an exact equation. Due to the difficulties in modeling electromagnetic systems, artificial intelligence-based studies have a special importance in this field. In this study, the multidimensional optimization of a compact microstrip monopole antenna that can be used in next generation communication applications is studied with a new artificial intelligence algorithm, the red fox algorithm. Thus, a compact microstrip antenna with broadband (8.75 GHz - 11.25 GHz) radiation at 10 GHz resonant frequency is designed for X-Band applications.",

keywords = "5G, 6G, RFO, optimization, pareto",

author = "Semih Pak and G{\"u}ne{\c s}er, \{M. Tahir\} and Cihat {\c S}eker",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 ; Conference date: 15-05-2024 Through 18-05-2024",

year = "2024",

doi = "10.1109/SIU61531.2024.10601083",

language = "T{\"u}rk{\c c}e",

series = "32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings",

address = "United States",

}

Pak, S, Güneşer, MT & Şeker, C 2024, Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı. in 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings. 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024, Mersin, Turkey, 15/05/24. https://doi.org/10.1109/SIU61531.2024.10601083

Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı. / Pak, Semih; Güneşer, M. Tahir; Şeker, Cihat.
32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2024. (32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı

AU - Pak, Semih

AU - Güneşer, M. Tahir

AU - Şeker, Cihat

PY - 2024

Y1 - 2024

N2 - Developments in artificial intelligence directly affect various fields of science. This is especially important in the solution of higher-order models and systems that do not have an exact equation. Due to the difficulties in modeling electromagnetic systems, artificial intelligence-based studies have a special importance in this field. In this study, the multidimensional optimization of a compact microstrip monopole antenna that can be used in next generation communication applications is studied with a new artificial intelligence algorithm, the red fox algorithm. Thus, a compact microstrip antenna with broadband (8.75 GHz - 11.25 GHz) radiation at 10 GHz resonant frequency is designed for X-Band applications.

AB - Developments in artificial intelligence directly affect various fields of science. This is especially important in the solution of higher-order models and systems that do not have an exact equation. Due to the difficulties in modeling electromagnetic systems, artificial intelligence-based studies have a special importance in this field. In this study, the multidimensional optimization of a compact microstrip monopole antenna that can be used in next generation communication applications is studied with a new artificial intelligence algorithm, the red fox algorithm. Thus, a compact microstrip antenna with broadband (8.75 GHz - 11.25 GHz) radiation at 10 GHz resonant frequency is designed for X-Band applications.

KW - 5G

KW - 6G

KW - RFO

KW - optimization

KW - pareto

UR - https://www.scopus.com/pages/publications/85200861845

U2 - 10.1109/SIU61531.2024.10601083

DO - 10.1109/SIU61531.2024.10601083

M3 - Konferans katkısı

AN - SCOPUS:85200861845

T3 - 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings

BT - 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024

Y2 - 15 May 2024 through 18 May 2024

ER -

Pak S, Güneşer MT, Şeker C. Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı. In 32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2024. (32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings). doi: 10.1109/SIU61531.2024.10601083

Kompakt Mikroşerit Monopol Anten Parametrelerinin NS-RFO ile Optimizasyonu ve Anten Tasarımında Yapay Zeka kullanımı

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap