Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models

Mahmud Esad Yiǧit; Gülay Öke Günel; Tayfun Günel

Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models

Mahmud Esad Yiǧit, Gülay Öke Günel, Tayfun Günel

Istanbul Technical University

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

4 Atıf (Scopus)

Özet

In this paper, a rectangular microstrip antenna which is conformed to a cylindrical surface is synthesized by using Genetic Algorithm (GA), Support Vector Regression (SVR) and Artificial Neural Networks (ANN). GA is used to obtain the desired resonant frequency via trained SVR and ANN models. The results obtained by SVR and ANN models are compared.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	1022-1026
Sayfa sayısı	5
ISBN (Elektronik)	9786050107371
Yayın durumu	Yayınlandı - 2 Tem 2017
Etkinlik	10th International Conference on Electrical and Electronics Engineering, ELECO 2017 - Bursa, Turkey Süre: 29 Kas 2017 → 2 Ara 2017

Yayın serisi

Adı	2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Hacim	2018-January

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

???event.eventtypes.event.conference???	10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Ülke/Bölge	Turkey
Şehir	Bursa
Periyot	29/11/17 → 2/12/17

Bibliyografik not

Publisher Copyright:
© 2017 EMO (Turkish Chamber of Electrical Enginners).

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Yiǧit, M. E., Günel, G. Ö., & Günel, T. (2017). Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models. In 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017 (pp. 1022-1026). (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Hac. 2018-January). Institute of Electrical and Electronics Engineers Inc..

Yiǧit, Mahmud Esad ; Günel, Gülay Öke ; Günel, Tayfun. / Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models. 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1022-1026 (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017).

@inproceedings{6eb6f6cf115043baa06bc890fc46f693,

title = "Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models",

abstract = "In this paper, a rectangular microstrip antenna which is conformed to a cylindrical surface is synthesized by using Genetic Algorithm (GA), Support Vector Regression (SVR) and Artificial Neural Networks (ANN). GA is used to obtain the desired resonant frequency via trained SVR and ANN models. The results obtained by SVR and ANN models are compared.",

author = "Yiǧit, {Mahmud Esad} and G{\"u}nel, {G{\"u}lay {\"O}ke} and Tayfun G{\"u}nel",

note = "Publisher Copyright: {\textcopyright} 2017 EMO (Turkish Chamber of Electrical Enginners).; 10th International Conference on Electrical and Electronics Engineering, ELECO 2017 ; Conference date: 29-11-2017 Through 02-12-2017",

year = "2017",

month = jul,

day = "2",

language = "English",

series = "2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017",

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

pages = "1022--1026",

booktitle = "2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017",

address = "United States",

}

Yiǧit, ME, Günel, GÖ & Günel, T 2017, Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models. in 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, hac. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1022-1026, 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, Bursa, Turkey, 29/11/17.

Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models. / Yiǧit, Mahmud Esad; Günel, Gülay Öke ; Günel, Tayfun.
2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1022-1026 (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Hac. 2018-January).

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

TY - GEN

T1 - Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models

AU - Yiǧit, Mahmud Esad

AU - Günel, Gülay Öke

AU - Günel, Tayfun

PY - 2017/7/2

Y1 - 2017/7/2

N2 - In this paper, a rectangular microstrip antenna which is conformed to a cylindrical surface is synthesized by using Genetic Algorithm (GA), Support Vector Regression (SVR) and Artificial Neural Networks (ANN). GA is used to obtain the desired resonant frequency via trained SVR and ANN models. The results obtained by SVR and ANN models are compared.

AB - In this paper, a rectangular microstrip antenna which is conformed to a cylindrical surface is synthesized by using Genetic Algorithm (GA), Support Vector Regression (SVR) and Artificial Neural Networks (ANN). GA is used to obtain the desired resonant frequency via trained SVR and ANN models. The results obtained by SVR and ANN models are compared.

UR - http://www.scopus.com/inward/record.url?scp=85046245687&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85046245687

T3 - 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017

SP - 1022

EP - 1026

BT - 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Conference on Electrical and Electronics Engineering, ELECO 2017

Y2 - 29 November 2017 through 2 December 2017

ER -

Yiǧit ME, Günel GÖ , Günel T. Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models. In 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1022-1026. (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017).

Genetic based approach to the synthesis of a cylindrical-rectangular microstrip conformal antenna using artificial neural network and Support Vector Regression models

Özet

Yayın serisi

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

Bibliyografik not

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap