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2022年讯飞开发者大赛-考虑时空依赖及全局要素的城市道路交通流量预测挑战赛-Top3解决方案

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iFLYTEK-Traffic-Flow-Challenge

The 3rd Place Solution iFLYTEK Traffic Flow Challenge

考虑时空依赖及全局要素的城市道路交通流量预测挑战赛——BUAA团队

Train

source train.sh

Test

source test.sh

Reference

[1] Bai L, Yao L, Li C, et al. Adaptive graph convolutional recurrent network for traffic forecasting[J]. Advances in neural information processing systems, 2020, 33: 17804-17815.

[2] Wang J, Jiang J, Jiang W, et al. Libcity: An open library for traffic prediction[C]//Proceedings of the 29th International Conference on Advances in Geographic Information Systems. 2021: 145-148.

Code Reference: LibCity

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2022年讯飞开发者大赛-考虑时空依赖及全局要素的城市道路交通流量预测挑战赛-Top3解决方案

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