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

Abstract

Artificial Neural Networks (ANNs) were used in this study to estimate the hourly passenger populations at certain stations in Istanbul. 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.