| Issue |
E3S Web of Conf.
Volume 531, 2024
Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2024)
|
|
|---|---|---|
| Article Number | 02012 | |
| Number of page(s) | 7 | |
| Section | Electric Mobility, Decarbonizing Energy Systems | |
| DOI | https://doi.org/10.1051/e3sconf/202453102012 | |
| Published online | 03 June 2024 | |
Forecasting transport flows using big data and machine learning technology
Tashkent State Transport University, Tashkent, Uzbekistan
* Corresponding author: tashmetov1993@gmail.com
Efficient management of urban transportation is crucial for addressing the growing challenges posed by increasing traffic and population. In this context, the utilization of big data and intelligent systems has become paramount. This paper introduces a comprehensive approach to traffic flow management at a key intersection in Tashkent, capitalizing on the integration of big data analytics and predictive model.
Key words: Big Data / machine learning / CRISP-DM / ITS / traffic flow / gradient boosting regressor / intersection / correlation / regression
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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