Journal of Contemporary Urban Affairs
Vol. 6 No. 2 (2022): Journal of Contemporary Urban Affairs

Data Mining as a Method for Comparison of Traffic Accidents in Şişli District of Istanbul

Ersen, Mert (Unknown)
Büyüklü, Ali Hakan (Unknown)
Taşabat, Semra Erpolat (Unknown)



Article Info

Publish Date
07 Jul 2022

Abstract

Studies to reduce traffic accidents are of great importance, especially for metropolitan cities. One of these metropolitan cities is undoubtedly Istanbul. In this study, a perspective on reducing traffic accidents was trying to be revealed by analyzing 3833 fatal and injury traffic accidents that occurred in the Şişli district of Istanbul between 2010-2017, with Data Mining (DM), Machine Learning (ML) and Geographic Information Systems methods (GIS), as well as traditional methods. It is aimed to visually determine the streets where traffic accidents are concentrated, to examine whether the accidents show anomalies according to the effect of the days of the week, to examine the differences according to the accidents that occur in the regions and to develop a model. For this purpose Kernel Density, decision trees, artificial neural networks, logistic regression and Naive Bayes methods were used. From the results obtained, it has been seen that some days are different from other days in terms of traffic accidents, according to the accident intensities and the performances of the modelling techniques used vary according to the regions. This study revealed that the ‘day of the week effect’ can also be applied to traffic accidents

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Journal Info

Abbrev

ijcua

Publisher

Subject

Description

The International Journal of Contemporary Urban Affairs (IJCUA) is the interdisciplinary academic, refereed journal which publishes two times a year by Anglo-American Publications LLC. IJCUA brings together all the theories, manifestoes and methodologies on contemporary urban spaces to raise the ...