Traffic congestion forecasting using machine learning methods
Background. This study develops a comprehensive approach to traffic congestion forecasting using synthetic data that simulates the dynamics of urban traffic. A hybrid methodology is proposed that combines time series analysis and deep learning, which is highly relevant for modeling nonlinear depende...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Science and Innovation Center Publishing House
2025-06-01
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| Series: | International Journal of Advanced Studies |
| Subjects: | |
| Online Access: | https://ijournal-as.com/jour/index.php/ijas/article/view/347 |
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