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https://doi.org/10.17559/TV-20170629201111

Arranging Bus Behaviour by Finding the Best Prediction Model with Artificial Neural Networks

Emrah Aydemir   ORCID icon orcid.org/0000-0002-8380-7891 ; Ahi Evran University, Yenice Mah. Terme Cad. No: 45 Merkez / Kirşehir, Turkey
Sevinc Gulsecen ; İstanbul University, Kalenderhane Mah. 16 Mart Şehitleri Cad. Dr. Şevket Apt. No: 8 PK 34134 Vezneciler-Beyazıt-Fatih/İstanbul, Turkey

Puni tekst: engleski, pdf (1 MB) str. 885-892 preuzimanja: 539* citiraj
APA 6th Edition
Aydemir, E. i Gulsecen, S. (2019). Arranging Bus Behaviour by Finding the Best Prediction Model with Artificial Neural Networks. Tehnički vjesnik, 26 (4), 885-892. https://doi.org/10.17559/TV-20170629201111
MLA 8th Edition
Aydemir, Emrah i Sevinc Gulsecen. "Arranging Bus Behaviour by Finding the Best Prediction Model with Artificial Neural Networks." Tehnički vjesnik, vol. 26, br. 4, 2019, str. 885-892. https://doi.org/10.17559/TV-20170629201111. Citirano 12.05.2021.
Chicago 17th Edition
Aydemir, Emrah i Sevinc Gulsecen. "Arranging Bus Behaviour by Finding the Best Prediction Model with Artificial Neural Networks." Tehnički vjesnik 26, br. 4 (2019): 885-892. https://doi.org/10.17559/TV-20170629201111
Harvard
Aydemir, E., i Gulsecen, S. (2019). 'Arranging Bus Behaviour by Finding the Best Prediction Model with Artificial Neural Networks', Tehnički vjesnik, 26(4), str. 885-892. https://doi.org/10.17559/TV-20170629201111
Vancouver
Aydemir E, Gulsecen S. Arranging Bus Behaviour by Finding the Best Prediction Model with Artificial Neural Networks. Tehnički vjesnik [Internet]. 2019 [pristupljeno 12.05.2021.];26(4):885-892. https://doi.org/10.17559/TV-20170629201111
IEEE
E. Aydemir i S. Gulsecen, "Arranging Bus Behaviour by Finding the Best Prediction Model with Artificial Neural Networks", Tehnički vjesnik, vol.26, br. 4, str. 885-892, 2019. [Online]. https://doi.org/10.17559/TV-20170629201111

Sažetak
Artificial Neural Networks (ANNs) were used in this study to estimate the hourly passenger populations at certain stations in İstanbul. To do this, the details were collected from various sources regarding the passengers in a station. This study aims to show what can be implemented for the passenger numbers in the decision support system and makes some recommendations for the regulation of the bus lines. Trials were conducted using an ANN with a backpropagation model and various inner layers for the estimations. The MAE score was 10.301 for the stations studied. Qualitative interviews were conducted with 32 passengers and 12 drivers, and solutions were searched for the density of the lines. A proposal system was developed with the c# software resulting from the combination of the prediction model with these proposals.

Ključne riječi
Artificial Neural Networks; estimation; İstanbul; public transportation

Hrčak ID: 223275

URI
https://hrcak.srce.hr/223275

Posjeta: 1.020 *