Advanced Machine Learning Approaches for Improving Traffic Flow Predictions in Smart Transportation Systems
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-51167-7_14
Reference8 articles.
1. Anirudh Ameya Kashyap, Shravan Raviraj, Ananya Devarakonda, Shamanth R, Nayak K, Santhosh K V & Soumya J Bhat | Fabio Galatioto (Reviewing editor) (2022) Traffic flow prediction models – A review of deep learning techniques, Cogent Eng., 9:1, https://doi.org/10.1080/23311916.2021.2010510
2. Y. Jia, J. Wu, M. Xu, Traffic flow prediction with rainfall impact using a deep learning method. J. Adv. Transp., Article ID 6575947, 10 (2017). https://doi.org/10.1155/2017/6575947
3. O. Mohammed, J. Kianfar, A Machine Learning Approach to Short-Term Traffic Flow Prediction: A Case Study of Interstate 64 in Missouri (2018 IEEE International Smart Cities Conference (ISC2), 2018), pp. 1–7. https://doi.org/10.1109/ISC2.2018.8656924
4. S.S. Sepasgozar, S. Pierre, Network traffic prediction model considering road traffic parameters using artificial intelligence methods in VANET. IEEE Access 10, 8227–8242 (2022). https://doi.org/10.1109/ACCESS.2022.3144112
5. A. Moussavi-Khalkhali, M. Jamshidi, L.B.E. Chair, Leveraging Machine Learning Algorithms to Perform Online and Offline Highway Traffic Flow Predictions (2014 13th International Conference on Machine Learning and Applications, 2014), pp. 419–423. https://doi.org/10.1109/ICMLA.2014.75
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