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

Authors

  • Ph.D. Candidate Mert Ersen Graduate School of Science and Engineering, Department of Statistics, 100/2000 YÖK Doctoral Scholarship Sustainable and Intelligent Transportation Sub-Department, Yıldız Technical University, Istanbul, Turkey https://orcid.org/0000-0001-5643-4690
  • Professor Dr. Ali Hakan Büyüklü Department of Statistics, Faculty of Art and Science, Yıldız Technical University, Turkey https://orcid.org/0000-0002-4174-4538
  • Professor Dr. Semra Erpolat Taşabat Department of Statistics, Faculty of Arts and Sciences, Mimar Sinan Fine Arts University, Turkey https://orcid.org/0000-0001-6845-8278

DOI:

https://doi.org/10.25034/ijcua.2022.v6n2-2

Keywords:

Geographic Information Systems, Kernel Density Method, Traffic Accidents, Decision Trees, Artificial Neural Networks, Logistic Regression, Naive Bayes

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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Author Biographies

Ph.D. Candidate Mert Ersen, Graduate School of Science and Engineering, Department of Statistics, 100/2000 YÖK Doctoral Scholarship Sustainable and Intelligent Transportation Sub-Department, Yıldız Technical University, Istanbul, Turkey

Mert Ersen is a PhD student at Yıldız Technical University, Graduate School of Science and Engineering, Department of Statistics. He is also a scholarship holder in YÖK 100/2000 Sustainable and Intelligent Transportation sub-department. His study titled “Analysis of Fatal and Injury Traffic Accidents in Istanbul Sariyer District with Spatial Statistics Methods” was published in the Sustainability journal. The author continues his studies on environment and transportation.

Professor Dr. Ali Hakan Büyüklü, Department of Statistics, Faculty of Art and Science, Yıldız Technical University, Turkey

Ali Hakan Büyüklü is a professor at Yıldız Technical University, Faculty of Arts and Sciences, Department of Statistics. The author was the head of the statistics department of Yıldız Technical University for many years, is interested in data mining, time series and econometrics. He is also a member of the water policy association. He has published enormous papers and contributed to an article on water policies in international journals. He has authored numerous articles among them we can highlight: 1-Applying the Hierarchical Gray Relational Clustering Method to Municipal Water Use in Turkey (2022), 2-Predicting monthly streamflow using a hybrid wavelet neural network: A case study of the Çoruh river basin (2021) and 3-Analysis of Fatal and Injury Traffic Accidents in Istanbul Sariyer District with Spatial Statistics Methods (2021).

Professor Dr. Semra Erpolat Taşabat, Department of Statistics, Faculty of Arts and Sciences, Mimar Sinan Fine Arts University, Turkey

Semra Erpolat Taşbat is a professor at Mimar Sinan Fine Arts University, Faculty of Arts and Sciences, Department of Statistics. The author, who is also a part-time professor at different universities, is interested in decision theory, applied statistics and data science. She has published enormous papers and contributed to articles on data science in international journals. She has authored numerous articles among them we can highlight: The European Journal of Research and Development (2022), A Novel Multicriteria Decision-Making Method Based on Distance, Similarity, and Correlation: DSC TOPSIS (2019) and Analysis of Fatal and Injury Traffic Accidents in Istanbul Sariyer District with Spatial Statistics Methods (2021).

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Published

2022-07-07

How to Cite

Ersen, M., Büyüklü, A. H., & Taşabat, S. E. (2022). Data Mining as a Method for Comparison of Traffic Accidents in Şişli District of Istanbul. Journal of Contemporary Urban Affairs, 6(2), 113–141. https://doi.org/10.25034/ijcua.2022.v6n2-2