Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması

Hüseyin Korkmaz; Mehmet Ali Ertürk; Mehmet Adak

doi:10.26650/JTL.2024.1444128

Araştırma Makalesi

A Comparison of the Performance of Ensemble Tree and Neural Networks for The Prediction of Traffic Accident Duration

Yıl 2024, Cilt: 9 Sayı: 1, 20 - 47, 17.05.2024

Hüseyin Korkmaz , Mehmet Ali Ertürk , Mehmet Adak

https://doi.org/10.26650/JTL.2024.1444128

Öz

Traffic accident duration is defined as the time difference between the occurrence and the return of the accident scene’s initial state. The aim of this paper is to predict the traffic accident duration based on traffic accident data in Istanbul with Ensemble Tree and Neural Networks methods and to compare the performance of these methods. The secondary aim of the paper is to identify the main factors affecting the accident duration. The accident data sets obtained from Istanbul Metropolitan Municipality and General Directorate of Security are used in this paper. The dataset includes 1.905 traffic accident records in Istanbul from 2013 to 2021. The data were analyzed within the scope of data mining. Statistical tests and machine learning algorithms were applied to the extracted data set and prediction of traffic accident duration was performed. R², MSE, RMSE and MAE metrics were used for the performance measures of the algorithms applied in this paper. It was found that the Ensemble Tree algorithm achieved an R-Square of 0.85 in training, while the Neural Networks algorithm performed better with 0.91 in testing.

Anahtar Kelimeler

Accident Duration, Intelligent Transportation Systems, Machine Learning, Neural Networks, Ensemble Tree

Kaynakça

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Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması

Yıl 2024, Cilt: 9 Sayı: 1, 20 - 47, 17.05.2024

Hüseyin Korkmaz , Mehmet Ali Ertürk , Mehmet Adak

https://doi.org/10.26650/JTL.2024.1444128

Öz

Trafik kaza süresi, bir kazanın meydana gelmesi ile kaza yerinin başlangıç durumuna dönmesi arasındaki zaman farkı olarak ifade edilmektedir. Bu araştırmanın birincil amacı İstanbul’daki trafik kaza verilerine dayalı olarak trafik kaza süresini Topluluk Ağacı ve Sinir Ağları yöntemleri ile tahmin etmek ve bu yöntemlerin performanslarını karşılaştırmaktır. Araştırmanın ikincil amacı ise trafik kaza süresini etkileyen temel faktörleri belirlemektir. Bu araştırmada İstanbul Büyükşehir Belediyesi ve Emniyet Genel Müdürlüğü kurumlarından elde edilen İstanbul’a ait kaza bilgisi veri setleri kullanılmıştır. Veri seti, 2013-2021 yılları arasındaki İstanbul’da gerçekleşen 1.905 trafik kaza kaydını içermektedir. Veriler, veri madenciliği kapsamında incelenmiştir. Ayıklanan veri setine istatistik testleri ve makine öğrenmesi algoritmalarından Topluluk Ağacı ve Sinir Ağları uygulanarak trafik kaza süresi tahmini gerçekleştirilmiştir. Bu araştırmada uygulanan algoritmaların performans ölçümleri için R², MSE, RMSE ve MAE metrikleri kullanılmıştır. Topluluk Ağacı algoritmasının eğitimde R-Kare: 0.85 ile başarılı bir performans elde ettiği, testte ise R-Kare: 0.91 ile Sinir Ağları algoritmasının daha iyi performans gösterdiği sonucuna ulaşılmıştır.

Anahtar Kelimeler

Kaza Süresi, Akıllı Ulaşım Sistemleri, Makine Öğrenmesi, Sinir Ağları, Topluluk Ağacı

Kaynakça

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Toplam 88 adet kaynakça vardır.

Ayrıntılar

Birincil Dil	Türkçe
Konular	Ulaşım, Lojistik ve Tedarik Zincirleri (Diğer)
Bölüm	Araştırma Makalesi
Yazarlar	Hüseyin Korkmaz 0000-0002-2438-6919 Mehmet Ali Ertürk 0000-0002-4030-1110 Mehmet Adak 0000-0002-7788-1227
Erken Görünüm Tarihi	5 Temmuz 2024
Yayımlanma Tarihi	17 Mayıs 2024
Gönderilme Tarihi	27 Şubat 2024
Kabul Tarihi	9 Nisan 2024
Yayımlandığı Sayı	Yıl 2024 Cilt: 9 Sayı: 1

Kaynak Göster

APA	Korkmaz, H., Ertürk, M. A., & Adak, M. (2024). Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması. Journal of Transportation and Logistics, 9(1), 20-47. https://doi.org/10.26650/JTL.2024.1444128
AMA	Korkmaz H, Ertürk MA, Adak M. Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması. JTL. Mayıs 2024;9(1):20-47. doi:10.26650/JTL.2024.1444128
Chicago	Korkmaz, Hüseyin, Mehmet Ali Ertürk, ve Mehmet Adak. “Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı Ve Sinir Ağları Performansının Karşılaştırılması”. Journal of Transportation and Logistics 9, sy. 1 (Mayıs 2024): 20-47. https://doi.org/10.26650/JTL.2024.1444128.
EndNote	Korkmaz H, Ertürk MA, Adak M (01 Mayıs 2024) Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması. Journal of Transportation and Logistics 9 1 20–47.
IEEE	H. Korkmaz, M. A. Ertürk, ve M. Adak, “Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması”, JTL, c. 9, sy. 1, ss. 20–47, 2024, doi: 10.26650/JTL.2024.1444128.
ISNAD	Korkmaz, Hüseyin vd. “Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı Ve Sinir Ağları Performansının Karşılaştırılması”. Journal of Transportation and Logistics 9/1 (Mayıs 2024), 20-47. https://doi.org/10.26650/JTL.2024.1444128.
JAMA	Korkmaz H, Ertürk MA, Adak M. Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması. JTL. 2024;9:20–47.
MLA	Korkmaz, Hüseyin vd. “Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı Ve Sinir Ağları Performansının Karşılaştırılması”. Journal of Transportation and Logistics, c. 9, sy. 1, 2024, ss. 20-47, doi:10.26650/JTL.2024.1444128.
Vancouver	Korkmaz H, Ertürk MA, Adak M. Trafik Kaza Süresinin Tahmini İçin Topluluk Ağacı ve Sinir Ağları Performansının Karşılaştırılması. JTL. 2024;9(1):20-47.

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The JTL is being published twice (in April and October of) a year, as an official international peer-reviewed journal of the School of Transportation and Logistics at Istanbul University.