DeepTSP: Deep traffic state prediction model based on large-scale empirical data Y Liu, C Lyu, Y Zhang, Z Liu, W Yu, X Qu Communications in Transportation Research 1, 100012, 2021 | 84 | 2021 |
Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform Y Liu, F Wu, C Lyu, S Li, J Ye, X Qu Transportation Research Part E: Logistics and Transportation Review 161, 102694, 2022 | 71 | 2022 |
Exploring a large-scale multi-modal transportation recommendation system Y Liu, C Lyu, Z Liu, J Cao Transportation Research Part C: Emerging Technologies 126, 103070, 2021 | 54 | 2021 |
A static bike repositioning model in a hub-and-spoke network framework D Huang, X Chen, Z Liu, C Lyu, S Wang, X Chen Transportation Research Part E: Logistics and Transportation Review 141, 102031, 2020 | 51 | 2020 |
A spatio‐temporal ensemble method for large‐scale traffic state prediction Y Liu, Z Liu, HL Vu, C Lyu Computer‐Aided Civil and Infrastructure Engineering 35 (1), 26-44, 2020 | 47 | 2020 |
Building personalized transportation model for online taxi-hailing demand prediction Z Liu, Y Liu, C Lyu, J Ye IEEE Transactions on Cybernetics 51 (9), 4602-4610, 2020 | 46 | 2020 |
Attention-based deep ensemble net for large-scale online taxi-hailing demand prediction Y Liu, Z Liu, C Lyu, J Ye IEEE transactions on intelligent transportation systems 21 (11), 4798-4807, 2019 | 45 | 2019 |
Automatic feature engineering for bus passenger flow prediction based on modular convolutional neural network Y Liu, C Lyu, X Liu, Z Liu IEEE Transactions on Intelligent Transportation Systems 22 (4), 2349-2358, 2020 | 38 | 2020 |
Spatio-temporal ensemble method for car-hailing demand prediction Y Liu, C Lyu, A Khadka, W Zhang, Z Liu IEEE Transactions on Intelligent Transportation Systems 21 (12), 5328-5333, 2019 | 37 | 2019 |
Building effective short video recommendation Y Liu, C Lyu, Z Liu, D Tao 2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW …, 2019 | 21 | 2019 |
Behavior2vector: Embedding users’ personalized travel behavior to Vector Y Liu, F Wu, C Lyu, X Liu, Z Liu IEEE Transactions on Intelligent Transportation Systems 23 (7), 8346-8355, 2021 | 20 | 2021 |
Gaussian process regression for transportation system estimation and prediction problems: the Deformation and a Hat Kernel Z Liu, C Lyu, J Huo, S Wang, J Chen IEEE Transactions on Intelligent Transportation Systems 23 (11), 22331-22342, 2022 | 17 | 2022 |
Modelling the energy consumption of electric vehicles under uncertain and small data conditions Y Liu, Q Zhang, C Lyu, Z Liu Transportation Research Part A: Policy and Practice 154, 313-328, 2021 | 17 | 2021 |
A partial-Fréchet-distance-based framework for bus route identification C Lyu, X Wu, Y Liu, Z Liu IEEE Transactions on Intelligent Transportation Systems 23 (7), 9275-9280, 2021 | 16 | 2021 |
A personalized recommendation system for multi-modal transportation systems F Wu, C Lyu, Y Liu Multimodal Transportation 1 (2), 100016, 2022 | 15 | 2022 |
Exploring multi-scale spatial relationship between built environment and public bicycle ridership C Lyu, Y Liu, Z Liu, X Wu, X Yang Journal of Transport and Land Use 13 (1), 447-467, 2020 | 15 | 2020 |
Quantify the road link performance and capacity using deep learning models J Huo, X Wu, C Lyu, W Zhang, Z Liu IEEE Transactions on Intelligent Transportation Systems 23 (10), 18581-18591, 2022 | 14 | 2022 |
A Gaussian-process-based data-driven traffic flow model and its application in road capacity analysis Z Liu, C Lyu, Z Wang, S Wang, P Liu, Q Meng IEEE Transactions on Intelligent Transportation Systems 24 (2), 1544-1563, 2023 | 10 | 2023 |
Station-level hourly bike demand prediction for dynamic repositioning in bike sharing systems X Wu, C Lyu, Z Wang, Z Liu Smart transportation systems 2019, 19-27, 2019 | 9 | 2019 |
A holistic data-driven framework for developing a complete profile of bus passengers S Chen, X Liu, C Lyu, L Vlacic, T Tang, Z Liu Transportation Research Part A: Policy and Practice 173, 103692, 2023 | 4 | 2023 |