一种动车组车载转向架防冰涂层
高广军, 汪馗, 赵世越, 宋子健, 周永灿, 曾捷, 张丹瑜. 一种动车组车载转向架防冰涂层[P]. 湖南省: CN111234587A, 2020-06-05.
高广军, 汪馗, 赵世越, 宋子健, 周永灿, 曾捷, 张丹瑜. 一种动车组车载转向架防冰涂层[P]. 湖南省: CN111234587A, 2020-06-05.
高广军, 汪馗, 赵世越, 宋子健, 周永灿, 曾捷, 张丹瑜. 一种动车组车载转向架防冰装置[P]. 湖南省: CN211999542U, 2020-11-24.
Tang, J., Zeng, J., Wang, Y., Yuan, H., Liu, F., & Huang, H. (2021). Traffic flow prediction on urban road network based on License Plate Recognition data: combining attention-LSTM with Genetic Algorithm. Transportmetrica A: Transport Science, 17(4), 1217-1243.
Tang, J., & Zeng, J. (2022). Spatiotemporal gated graph attention network for urban traffic flow prediction based on license plate recognition data. Computer‐Aided Civil and Infrastructure Engineering, 37(1), 3-23.
吉柯, 唐进君, 曾捷 & 刘鑫源. (2023). 基于递阶优化的城市区域路网交通控制. 铁道科学与工程学报 (01), 63-73. doi:10.19713/j.cnki.43-1423/u.t20220242.
Zeng, J., Xiong, Y., Liu, F., Ye, J., & Tang, J. (2022). Uncovering the spatiotemporal patterns of traffic congestion from large-scale trajectory data: A complex network approach. Physica A: Statistical Mechanics and its Applications, 604, 127871.
Zeng, J., Tang, J., 2022. Combining knowledge graph into metro passenger flow prediction: a split-attention relational graph convolutional network. Expert Syst. Appl. 118790. doi:10.1016/j.eswa.2022.118790.
唐进君, 曾捷 & 段一鑫. (2022). 数据驱动的城市路网短时交通流预测. 武汉理工大学学报(交通科学与工程版) (05), 782-791+796.
Zeng, J., & Tang, J. (2022). Modeling Dynamic Traffic Flow as Visibility Graphs: A Network-Scale Prediction Framework for Lane-Level Traffic Flow Based on LPR Data. IEEE Transactions on Intelligent Transportation Systems, 1–16.
Li, M., Tang, J., Zeng, J., & Huang, H. (2023). A Kriging-based optimization method for meeting point locations to enhance flex-route transit services. Transportmetrica B: Transport Dynamics, 11 (1), 1281-1310.
唐进君,吉柯,曾捷. 融合路径选择行为的路网交通控制方法、装置及存储介质[P]. 湖南省: CN116189426A, 2023-05-30.
陈浩, 刘飞扬, 唐进君, 曾捷 & 潘晓艺. (2023). 考虑内在关联性的城市路网交通运行效率评价. 测绘科学 (07), 227-234. doi:10.16251/j.cnki.1009-2307.2023.07.026.
唐进君,曾捷. 一种地铁客流预测方法、装置及计算机存储介质[P]. 湖南省: CN113239198B, 2023-10-31.
Dai, G., Tang, J., Zeng, J., Hu, C., & Zhao, C. (2024). Road network traffic flow prediction: A personalized federated learning method based on client reputation. Computers and Electrical Engineering, 120, 109678.
Hu, L., Tang, J., Zou, G., Li, Z., Zeng, J., & Li, M. (2025). Simulation optimization of highway hard shoulder running based on multi-agent deep deterministic policy gradient algorithm. Alexandria Engineering Journal, 117(November 2024), 99–115. https://doi.org/10.1016/j.aej.2024.12.110.
Zeng, J., Xiao, C., Tang, J. & Hu, C. (2025).Inquiring the Next Location and Travel Time: A Deep Learning Based Temporal Point Process for Vehicle Trajectory Prediction. IEEE Internet of Things.
Dai, G., Tang, J., Zeng, J., & Jiang, Y. (2025). Short‐Term Passenger Flow Prediction Based on Federated Learning on the Urban Metro System. Journal of Advanced Transportation, 2025(1), 8834513.
Hu, L., Tang, J., Wang, Z., Li, Z., Li, M., & Zeng, J. (2025). Optimization of hard shoulder running on highways using multi-agent reinforcement learning considering emergency vehicles. Journal of Intelligent Transportation Systems, 1-22.
Hu, C., Tang, J., Hu, J., Wang, Y., Li, Z., Zeng, J., & Han, C. (2025). Dynamic partitioning of heterogeneously loaded road networks: A two-level regionalization scheme with Monte Carlo tree search. Transportation Research Part C: Emerging Technologies. https://www.sciencedirect.com/science/article/pii/S0968090X25003456.
Reviewer of ACM Computing Surveys, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicular Technology, Cities, Engineering Applications of Artificial Intelligence, Complex & Intelligent Systems, Journal of Advanced Transportation, Journal of Traffic and Transportation Engineering (English Edition), The Journal of Supercomputing, Plos ONE, IEEE Access, IET Networks, World Transport Convention (WTC), COTA CICTP.