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Efficient traffic management is crucial for maintaining urban mobility, especially in densely populated areas where congestion, accidents, and delays can lead to frustrating and expensive commutes.
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M. Liu, J. Wu, Y. Wang, and L. He, “Traffic flow prediction based on deep learning,” Journal of System Simulation , vol. 30, no. 11, p. 4100, 2018
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2018
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2018
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2018
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2018
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B. Yu, H. Yin, and Z. Zhu, “Spatio-temporal graph convolutional networks: a deep learning framework for traffic forecasting,” in Proceedings of the 27th International Joint Conference on Artificial Intelligence , 2018, pp. 3634–3640
2018
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P. A. Lopez, M. Behrisch, L. Bieker-Walz, J. Erdmann, Y.-P. Flötteröd, R. Hilbrich, L. Lücken, J. Rummel, P. Wagner, and E. Wießner, “Microscopic traffic simulation using sumo,” in 2018 21st international conference on intelligent transportation systems (ITSC) . IEEE, 2018, pp. 2575–2582
2018
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2019
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2020
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L. Bai, L. Yao, C. Li, X. Wang, and C. Wang, “Adaptive graph convolutional recurrent network for traffic forecasting,” Advances in neural information processing systems , vol. 33, pp. 17 804–17 815, 2020
2020
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2021
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C. Tian and W. K. Chan, “Spatial-temporal attention wavenet: A deep learning framework for traffic prediction considering spatial-temporal dependencies,” IET Intelligent Transport Systems , vol. 15, no. 4, pp. 549–561, 2021
2021
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M. Li and Z. Zhu, “Spatial-temporal fusion graph neural networks for traffic flow forecasting,” in Proceedings of the AAAI conference on artificial intelligence , vol. 35, no. 5, 2021, pp. 4189–4196
2021
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2021
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Z. Fang, Q. Long, G. Song, and K. Xie, “Spatial-temporal graph ode networks for traffic flow forecasting,” in Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining , 2021, pp. 364–373
2021
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W. Jiang, “Cellular traffic prediction with machine learning: A survey,” Expert Systems with Applications , p. 117163, 2022
2022
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I. Lohrasbinasab, A. Shahraki, A. Taherkordi, and A. Delia Jurcut, “From statistical-to machine learning-based network traffic prediction,” Transactions on Emerging Telecommunications Technologies , vol. 33, no. 4, p. e4394, 2022
2022
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Y. Chen and M. J. Zuo, “A sparse multivariate time series model-based fault detection method for gearboxes under variable speed condition,” Mechanical Systems and Signal Processing , vol. 167, p. 108539, 2022
2022
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B. D. Lund and T. Wang, “Chatting about chatgpt: how may ai and gpt impact academia and libraries?” Library Hi Tech News , vol. 40, no. 3, pp. 26–29, 2023
2023
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