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Traffic forecasting is crucial for intelligent transportation systems (ITS), aiding in efficient resource allocation and effective traffic control.
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L. Han, B. Du, L. Sun, Y. Fu, Y. Lv, and H. Xiong, “Dynamic and multi-faceted spatio-temporal deep learning for traffic speed forecasting,” in Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining , 2021, pp. 547–555
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B. Wang, Y. Zhang, X. Wang, P. Wang, Z. Zhou, L. Bai, and Y. Wang, “Pattern expansion and consolidation on evolving graphs for continual traffic prediction,” in Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , 2023, pp. 2223–2232
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Z. Liu, G. Zheng, and Y. Yu, “Cross-city few-shot traffic forecasting via traffic pattern bank,” in Proceedings of the 32nd ACM International Conference on Information and Knowledge Management , 2023, pp. 1451–1460
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A. Zeng, M. Chen, L. Zhang, and Q. Xu, “Are transformers effective for time series forecasting?” in Proceedings of the AAAI conference on artificial intelligence , vol. 37, no. 9, 2023, pp. 11 121–11 128
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