Yıl: 2020 Cilt: 7 Sayı: 3 Sayfa Aralığı: 1496 - 1508 Metin Dili: İngilizce DOI: 10.31202/ecjse.773088 İndeks Tarihi: 07-01-2021

Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network

Öz:
The forecasting of merging road traffic volume is one of the critical issues for the main networks oftraffic-congestion suffering cities. Artificial neural network (ANN) – used in many disciplines varying fromeconomy to different engineering applications such as sales forecasting, industrial process control, customerresearch, data validation, risk management, target marketing and civil engineering – could be a promisingsolution to this issue. Providing a higher forecasting accuracy based on past traffic data, ANN has become verypopular in transportation engineering for the last 30 years. In this paper, the main goal was to predict the shortterm traffic volume of a connection road leading to one of Istanbul’s Bosphorous Bridge in Turkey by the threedifferent implementations of ANN. These were Feed Forward Back Propagation (FFBP), Generalized RegressionNeural Network (GRNN) and Radial Based Function (RBF). Then, obtained results were compared with eachother and the result of Multi Linear Regression (MLR) method.
Anahtar Kelime:

Tali Yollar için Kısa Vadeli Trafik Hacminin Yapay Sinir Ağlarıyla Belirlenmesi

Öz:
Ana arterlerinde trafik sıkışıklığı yaşanan şehirlerin ikincil derecedeki yollarında trafik hacim tahminlerinin yapılması kritik konulardan biridir. Ekonomiden farklı mühendislik uygulamalarına kadar birçok alanda (satış tahminleri, endüstriyel süreç kontrolü, müşteri araştırmaları, veri doğrulama, risk yönetimi, hedef pazarlama ve inşaat mühendisliği gibi) kullanılan yapay sinir ağı (YSA) bu konuda umut verici bir çözüm olabilir. Geçmiş trafik verilerine dayanarak daha yüksek bir tahmin doğruluğu sağlayan YSA, son 30 yıldır ulaştırma mühendisliği alanındaki uygulamalarda çok popüler hale geldi. Bu makaledeki temel amaç, İstanbul'un Boğaz Köprülerinden birine katılan bir bağlantı yolunun kısa dönem trafik hacmini YSA'nın üç farklı uygulamasıyla tahmin etmektir. Bunlar İleri Besleme Geri Yayılımı (FFBP), Genelleştirilmiş Regresyon Sinir Ağı (GRNN) ve Radyal Tabanlı Fonksiyon (RBF) idi. Daha sonra elde edilen sonuçlar birbirleriyle ve Çoklu Doğrusal Regresyon (MLR) yönteminin sonuçları ile karşılaştırıldı.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
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APA gedik a (2020). Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. , 1496 - 1508. 10.31202/ecjse.773088
Chicago gedik abdulgazi Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. (2020): 1496 - 1508. 10.31202/ecjse.773088
MLA gedik abdulgazi Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. , 2020, ss.1496 - 1508. 10.31202/ecjse.773088
AMA gedik a Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. . 2020; 1496 - 1508. 10.31202/ecjse.773088
Vancouver gedik a Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. . 2020; 1496 - 1508. 10.31202/ecjse.773088
IEEE gedik a "Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network." , ss.1496 - 1508, 2020. 10.31202/ecjse.773088
ISNAD gedik, abdulgazi. "Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network". (2020), 1496-1508. https://doi.org/10.31202/ecjse.773088
APA gedik a (2020). Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. El-Cezerî Journal of Science and Engineering, 7(3), 1496 - 1508. 10.31202/ecjse.773088
Chicago gedik abdulgazi Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. El-Cezerî Journal of Science and Engineering 7, no.3 (2020): 1496 - 1508. 10.31202/ecjse.773088
MLA gedik abdulgazi Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. El-Cezerî Journal of Science and Engineering, vol.7, no.3, 2020, ss.1496 - 1508. 10.31202/ecjse.773088
AMA gedik a Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. El-Cezerî Journal of Science and Engineering. 2020; 7(3): 1496 - 1508. 10.31202/ecjse.773088
Vancouver gedik a Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network. El-Cezerî Journal of Science and Engineering. 2020; 7(3): 1496 - 1508. 10.31202/ecjse.773088
IEEE gedik a "Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network." El-Cezerî Journal of Science and Engineering, 7, ss.1496 - 1508, 2020. 10.31202/ecjse.773088
ISNAD gedik, abdulgazi. "Short-term Traffic Volume Prediction for the Merging Roads by Artificial Neural Network". El-Cezerî Journal of Science and Engineering 7/3 (2020), 1496-1508. https://doi.org/10.31202/ecjse.773088