Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim

Guzide Miray Perihanoǧlu; Himmet Karaman

doi:10.1109/SIU59756.2023.10223770

Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim

Guzide Miray Perihanoǧlu, Himmet Karaman

Geomatik Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

Özet

Estimation of path loss in communication systems is a fundamental requirement for designing any mobile or wireless communication system and assessing the quality of service. In this study, Random Forest machine regression algorithm and GIS based path loss estimation method for 1800 and 2100 MHz in Van Yüzüncü Yil University campus area are proposed. The goal of this model is to predict the coverage area, visualize the predicted signal path loss and analyze the field strength coverage. In order to increase the training efficiency of the model, the selected parameter values are structured according to the performance metrics. Based on the preliminary information obtained from the measured results, a series of training sets were created. According to the experimental results, it was observed that the Random Forest and GIS-based model performed effectively in different terrain classes for path loss estimation.

Tercüme edilen katkı başlığı	Geographic Information Systems (GIS) and Random Forests Regression-Based Approach for Path Loss Prediction in the Campus Environment
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9798350343557
DOI'lar	https://doi.org/10.1109/SIU59756.2023.10223770
Yayın durumu	Yayınlandı - 2023
Etkinlik	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 - Istanbul, Turkey Süre: 5 Tem 2023 → 8 Tem 2023

Yayın serisi

Adı	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

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

???event.eventtypes.event.conference???	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Ülke/Bölge	Turkey
Şehir	Istanbul
Periyot	5/07/23 → 8/07/23

Bibliyografik not

Publisher Copyright:
© 2023 IEEE.

Keywords

Geographic information systems(GIS)
Path loss model
Random forests regression

Belgeye Erişim

10.1109/SIU59756.2023.10223770

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Perihanoǧlu, G. M., & Karaman, H. (2023). Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim. In 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU59756.2023.10223770

Perihanoǧlu, Guzide Miray ; Karaman, Himmet. / Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim. 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023).

@inproceedings{dad9d505c27649caa506644b65d4cf0d,

title = "Kamp{\"u}s Ortaminda Yol Kaybi Tahmini i{\c c}in Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yakla{\c s}im",

abstract = "Estimation of path loss in communication systems is a fundamental requirement for designing any mobile or wireless communication system and assessing the quality of service. In this study, Random Forest machine regression algorithm and GIS based path loss estimation method for 1800 and 2100 MHz in Van Y{\"u}z{\"u}nc{\"u} Yil University campus area are proposed. The goal of this model is to predict the coverage area, visualize the predicted signal path loss and analyze the field strength coverage. In order to increase the training efficiency of the model, the selected parameter values are structured according to the performance metrics. Based on the preliminary information obtained from the measured results, a series of training sets were created. According to the experimental results, it was observed that the Random Forest and GIS-based model performed effectively in different terrain classes for path loss estimation.",

keywords = "Geographic information systems(GIS), Path loss model, Random forests regression",

author = "Perihanoǧlu, {Guzide Miray} and Himmet Karaman",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 ; Conference date: 05-07-2023 Through 08-07-2023",

year = "2023",

doi = "10.1109/SIU59756.2023.10223770",

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

series = "31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023",

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

booktitle = "31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023",

address = "United States",

}

Perihanoǧlu, GM & Karaman, H 2023, Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim. in 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023, Institute of Electrical and Electronics Engineers Inc., 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023, Istanbul, Turkey, 5/07/23. https://doi.org/10.1109/SIU59756.2023.10223770

Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim. / Perihanoǧlu, Guzide Miray; Karaman, Himmet.
31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim

AU - Perihanoǧlu, Guzide Miray

AU - Karaman, Himmet

PY - 2023

Y1 - 2023

N2 - Estimation of path loss in communication systems is a fundamental requirement for designing any mobile or wireless communication system and assessing the quality of service. In this study, Random Forest machine regression algorithm and GIS based path loss estimation method for 1800 and 2100 MHz in Van Yüzüncü Yil University campus area are proposed. The goal of this model is to predict the coverage area, visualize the predicted signal path loss and analyze the field strength coverage. In order to increase the training efficiency of the model, the selected parameter values are structured according to the performance metrics. Based on the preliminary information obtained from the measured results, a series of training sets were created. According to the experimental results, it was observed that the Random Forest and GIS-based model performed effectively in different terrain classes for path loss estimation.

AB - Estimation of path loss in communication systems is a fundamental requirement for designing any mobile or wireless communication system and assessing the quality of service. In this study, Random Forest machine regression algorithm and GIS based path loss estimation method for 1800 and 2100 MHz in Van Yüzüncü Yil University campus area are proposed. The goal of this model is to predict the coverage area, visualize the predicted signal path loss and analyze the field strength coverage. In order to increase the training efficiency of the model, the selected parameter values are structured according to the performance metrics. Based on the preliminary information obtained from the measured results, a series of training sets were created. According to the experimental results, it was observed that the Random Forest and GIS-based model performed effectively in different terrain classes for path loss estimation.

KW - Geographic information systems(GIS)

KW - Path loss model

KW - Random forests regression

UR - http://www.scopus.com/inward/record.url?scp=85173430160&partnerID=8YFLogxK

U2 - 10.1109/SIU59756.2023.10223770

DO - 10.1109/SIU59756.2023.10223770

M3 - Konferans katkısı

AN - SCOPUS:85173430160

T3 - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

BT - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

Y2 - 5 July 2023 through 8 July 2023

ER -

Perihanoǧlu GM, Karaman H. Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim. In 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023). doi: 10.1109/SIU59756.2023.10223770

Kampüs Ortaminda Yol Kaybi Tahmini için Coǧrafi Bilgi Sistemleri (CBS) ve Rastgele Orman Regresyonu Tabanli Yaklaşim

Özet

Yayın serisi

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

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap