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[2] Zhihong Li, Xiaoyu Wang, Hua Cai,  et.al.. Novel Hybrid Spatiotemporal Convolution Neural Network Model for Short-Term Passenger Flow Prediction in a Large-Scale Metro System. Journal of Transportation Engineering Part A-systems, 2024

[3] Xia Zhao, Yuan Gao, Zhihong Li, et..al.IEF-BT-GCN: A High-Precision Rail Transit Passenger Flow Prediction Model with Complex External Factors. IEEE International Conference on Intelligent Transportation Systems. 2024

[4] Xia Zhao, Zhihong Li, et..al. Unraveling the Propagation Dynamics of Passenger Congestion in Public Transportation Systems Using Big Smart Card Data. International Journal of General Systems. 2024

[5] 李之红等，基于混合机器学习框架的网约车订单需求预测与异常点识别，交通信息与安全，2023

[6] Wen YJ, Li ZH, et.al.. RPConvformer: A novel Transformer-based deep neural networks for traffic flow prediction.EXPERT SYSTEMS WITH APPLICATIONS,2023

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[8] Zhihong Li et.al.. Fusion attention mechanism bidirectional LSTM for short-term traffic flow prediction. Journal of Intelligent Transportation Systems, 2022, 51(7): 1-14.

[9] Zhihong Li, Jing Zhang, Yanjie Wen,Yang Dong, Wangtu Xu ; A Multiscale Fusion YOLOV3-Based Model for Human Abnormal Behavior Detection in Special Scenarios, Journal of Transportation Engineering, Part A: Systems, 2022, 149(2): 04022150-1-04022150-12

[10] Zhihong Li, Wangtu Xu. Pedestrian evacuation within limited-space buildings based on different exit design schemes[J],Safety Science , 2020.4（SCI 中科院1区Top）

[11] Zhihong Li, Wangtu Xu. Path decision modelling for passengers in the urban rail transit hub under the guidance of traffic signs[J]，Journal of Ambient Intelligence and Humanized Computing, 2019.10（SCI）

[12] Li, Zhihong; Dong, Yang; Wen, Yanjie; Xu, Han; Wu, Jiahao ; A Deep Pedestrian Tracking SSD-Based Model in the Sudden Emergency or Violent Environment, Journal of Advanced Transportation,2021, 2021: p.2085876.

[13] Lizhihong；Xu Han; Qiu Shiyao; Liu Jun; Yang Kairan; Wu Jiahao. Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data. Journal of Advanced Transportation, 2022. 2022: p. 7064061.

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[17] 李之红,袁振洲,许旺土.综合货运网络规模及货物周转量算法研究［J］.北京交通大学学报,2014 38(175)： 03 36-41+47.

[18] 李之红,郄堃,王健宇,等.建成环境影响下的城市轨道交通客流多步短时预测[J/OL].交通运输系统工程与信息,1-16[2025-01-22].