MFAGCN: Multi-Feature Based Attention Graph Convolutional Network for Traffic Prediction. - Haoran Li; Jianbo Li; Zhiqiang Lv; Zhihao Xu 002 (WASA (1), 2021)

Parallel Computing of Spatio-Temporal Model Based on Deep Reinforcement Learning. - Zhiqiang Lv; Jianbo Li; Zhihao Xu 002; Yue Wang 052; Haoran Li (WASA (1), 2021)

DDCAttNet: Road Segmentation Network for Remote Sensing Images. - Genji Yuan; Jianbo Li; Zhiqiang Lv; Yinong Li; Zhihao Xu 002 (WASA (2), 2021)

A graph spatial-temporal model for predicting population density of key areas. - Zhihao Xu 002; Jianbo Li; Zhiqiang Lv; Yue Wang 052; Liping Fu; Xinghao Wang (Comput. Electr. Eng., 2021)

Deep learning in the COVID-19 epidemic: A deep model for urban traffic revitalization index. - Zhiqiang Lv; Jianbo Li; Chuanhao Dong; Haoran Li; Zhihao Xu 002 (Data Knowl. Eng., 2021)

DeepPTP: A Deep Pedestrian Trajectory Prediction Model for Traffic Intersection. - Zhiqiang Lv; Jianbo Li; Chuanhao Dong; Yue Wang 052; Haoran Li; Zhihao Xu 002 (KSII Trans. Internet Inf. Syst., 2021)

Blind Travel Prediction Based on Obstacle Avoidance in Indoor Scene. - Zhiqiang Lv; Jianbo Li; Haoran Li; Zhihao Xu 002; Yue Wang 052 (Wirel. Commun. Mob. Comput., 2021)

DDFM: A Novel Perspective on Urban Travel Demand Forecasting Based on the Ensemble Empirical Mode Decomposition and Deep Learning. - Rongkun Ye; Zhihao Xu 002; Junjie Pang (ICBDT, 2022)

Prediction of Cancellation Probability of Online Car-Hailing Orders Based on Multi-source Heterogeneous Data Fusion. - Haokai Sun 002; Zhiqiang Lv; Jianbo Li; Zhihao Xu 002; Zhaoyu Sheng; Zhaobin Ma (WASA (2), 2022)

A Novel Perspective on Travel Demand Prediction Considering Natural Environmental and Socioeconomic Factors. - Zhihao Xu 002; Zhiqiang Lv; Jianbo Li; Haokai Sun 002; Zhaoyu Sheng (IEEE Intell. Transp. Syst. Mag., 2023)

Taxi travel time prediction based on fusion of traffic condition features. - Zhaoyu Sheng; Zhiqiang Lv; Jianbo Li; Zhihao Xu 002; Haokai Sun 002; Xue Liu; Rongkun Ye (Comput. Electr. Eng., 2023)

DeepSTF: A Deep Spatial-Temporal Forecast Model of Taxi Flow. - Zhiqiang Lv; Jianbo Li; Chuanhao Dong; Zhihao Xu 002 (Comput. J., 2023)

Traffic Flow Forecasting in the COVID-19: A Deep Spatial-temporal Model Based on Discrete Wavelet Transformation. - Haoran Li; Zhiqiang Lv; Jianbo Li; Zhihao Xu 002; Yue Wang 052; Haokai Sun 002; Zhaoyu Sheng (ACM Trans. Knowl. Discov. Data, 2023)

GASTO: A Fast Adaptive Graph Learning Framework for Edge Computing Empowered Task Offloading. - Yinong Li; Jianbo Li; Zhiqiang Lv; Haoran Li; Yue Wang 052; Zhihao Xu 002 (IEEE Trans. Netw. Serv. Manag., 2023)

A new approach to COVID-19 data mining: A deep spatial-temporal prediction model based on tree structure for traffic revitalization index. - Zhiqiang Lv; Xiaotong Wang; Zesheng Cheng; Jianbo Li; Haoran Li; Zhihao Xu 002 (Data Knowl. Eng., 2023)

Deep spatial-temporal travel time prediction model based on trajectory feature. - Zhaoyu Sheng; Zhiqiang Lv; Jianbo Li; Zhihao Xu 002 (Comput. Electr. Eng., 2023)

Fast autoregressive tensor decomposition for online real-time traffic flow prediction. - Zhihao Xu 002; Zhiqiang Lv; Benjia Chu; Jianbo Li (Knowl. Based Syst., 2023)

Meta Analysis of Traffic Safety Prediction. - Hongyu Yan; Jianbo Li; Zhihao Xu 002; Zhiqiang Lv (CBD, 2024)

MT-CNN: A Lightweight Spatial-Temporal Convolutional Neural Network for Deep Learning of Complex Trajectory Distributions based on Area Partitioning. - Rongkun Ye; Zhiqiang Lv; Zhihao Xu 002; Jianbo Li (IJCNN, 2024)

Progress and prospects of future urban health status prediction. - Zhihao Xu 002; Zhiqiang Lv; Benjia Chu; Zhaoyu Sheng; Jianbo Li (Eng. Appl. Artif. Intell., 2024)

Optimization of spatial-temporal graph: A taxi demand forecasting model based on spatial-temporal tree. - Jianbo Li; Zhiqiang Lv; Zhaobin Ma; Xiaotong Wang; Zhihao Xu 002 (Inf. Fusion, 2024)

TreeCN: Time Series Prediction With the Tree Convolutional Network for Traffic Prediction. - Zhiqiang Lv; Zesheng Cheng; Jianbo Li; Zhihao Xu 002; Zheng Yang 002 (IEEE Trans. Intell. Transp. Syst., 2024)

Shared mobility demand prediction via A fast spatiotemporal tensor autoregression. - Hongyu Yan; Zhiqiang Lv; Jianbo Li; Benjia Chu; Zhihao Xu 002 (Eng. Appl. Artif. Intell., 2025)

HT-STNet: a hierarchical Tucker decomposition and spatio-temporal LSTM network for accurate and efficient shared mobility demand forecasting on sparse data. - Hongyu Yan; Jianbo Li; Benjia Chu; Zhihao Xu 002 (Appl. Intell., 2025)