| Smart fog based workflow for traffic control networks Q Wu, J Shen, B Yong, J Wu, F Li, J Wang, Q Zhou Future Generation Computer Systems 97, 825-835, 2019 | 32 | 2019 |
| Distributed agent-based deep reinforcement learning for large scale traffic signal control Q Wu, J Wu, J Shen, B Du, A Telikani, M Fahmideh, C Liang Knowledge-Based Systems 241, 108304, 2022 | 29 | 2022 |
| An energy aware offloading scheme for interdependent applications in software-defined IoV with fog computing architecture Y Zhai, W Sun, J Wu, L Zhu, J Shen, X Du, M Guizani IEEE Transactions on Intelligent Transportation Systems 22 (6), 3813-3823, 2020 | 27 | 2020 |
| Ensemble machine learning systems for the estimation of steel quality control F Li, J Wu, F Dong, J Lin, G Sun, H Chen, J Shen 2018 IEEE International Conference on Big Data (Big Data), 2245-2252, 2018 | 27 | 2018 |
| Towards Attention-Based Convolutional Long Short-Term Memory for Travel Time Prediction of Bus Journeys J Wu, Q Wu, J Shen, C Cai Sensors 20 (12), 3354, 2020 | 26 | 2020 |
| A secure traffic police remote sensing approach via a deep learning-based low-altitude vehicle speed detector through uavs in smart cites: Algorithm, implementation and evaluation AJ Moshayedi, AS Roy, A Taravet, L Liao, J Wu, M Gheisari Future Transportation 3 (1), 189-209, 2023 | 22 | 2023 |
| SATP-GAN: Self-attention based generative adversarial network for traffic flow prediction L Zhang, J Wu, J Shen, M Chen, R Wang, X Zhou, C Xu, Q Yao, Q Wu Transportmetrica B: Transport Dynamics 9 (1), 552-568, 2021 | 22 | 2021 |
| An Edge Based Multi-Agent Auto Communication Method for Traffic Light Control Q Wu, J Wu, J Shen, B Yong, Q Zhou Sensors 20 (15), 4291, 2020 | 18 | 2020 |
| Towards a general prediction system for the primary delay in urban railways J Wu, L Zhou, C Cai, F Dong, J Shen, G Sun 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 3482-3487, 2019 | 17 | 2019 |
| Expression might be enough: Representing pressure and demand for reinforcement learning based traffic signal control L Zhang, Q Wu, J Shen, L Lü, B Du, J Wu International Conference on Machine Learning, 26645-26654, 2022 | 16 | 2022 |
| Data fusion for MaaS: Opportunities and challenges J Wu, L Zhou, C Cai, J Shen, SK Lau, J Yong 2018 IEEE 22nd International Conference on Computer Supported Cooperative …, 2018 | 12 | 2018 |
| The Bounds of Improvements Toward Real-Time Forecast of Multi-Scenario Train Delays J Wu, Y Wang, B Du, Q Wu, Y Zhai, J Shen, L Zhou, C Cai, W Wei, Q Zhou IEEE Transactions on Intelligent Transportation Systems 23 (3), 2445 - 2456, 2022 | 10 | 2022 |
| A study on the dependability of software defined networks J Wu, Y Huang, J Kong, Q Tang, X Huang 2015 International Conference on Materials Engineering and Information …, 2015 | 8 | 2015 |
| A Multi-Task Graph Neural Network with Variational Graph Auto-Encoders for Session-Based Travel Packages Recommendation G Zhu, J Cao, L Chen, Y Wang, Z Bu, S Yang, J Wu, Z Wang ACM Transactions on the Web 17 (3), 1-30, 2023 | 5 | 2023 |
| A GTFS data acquisition and processing framework and its application to train delay prediction J Wu, B Du, Z Gong, Q Wu, J Shen, L Zhou, C Cai International Journal of Transportation Science and Technology 12 (1), 201-216, 2023 | 5 | 2023 |
| A novel Monte Carlo-based neural network model for electricity load forecasting B Yong, Z Xu, J Shen, H Chen, J Wu, F Li, Q Zhou International Journal of Embedded Systems 12 (4), 522-533, 2020 | 5 | 2020 |
| A hybrid LSTM-CPS approach for long-term prediction of train delays in multivariate time series J Wu, B Du, Q Wu, J Shen, L Zhou, C Cai, Y Zhai, W Wei, Q Zhou Future Transportation 1 (3), 765-776, 2021 | 4 | 2021 |
| Communicate with traffic lights and vehicles based on multi-agent reinforcement learning Q Wu, P Zhi, Y Wei, L Zhang, J Wu, Q Zhou, Q Zhou, P Gao 2021 IEEE 24th International Conference on Computer Supported Cooperative …, 2021 | 4 | 2021 |
| Multi-agent deep reinforcement learning for traffic signal control with Nash Equilibrium W Wei, Q Wu, J Wu, B Du, J Shen, T Li 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th …, 2021 | 3 | 2021 |
| Multivariate Multi-Step Train Delay Forecasting: A Hybrid LSTM-CPS Solution J Wu, Q Wu, L Zhou, C Cai, B Du, Y Zhai, W Wei, J Shen, Q Zhou Transportation Research Board 100th Annual MeetingTransportation Research Board, 2021 | 3 | 2021 |
Jun ShenUniversity of WollongongVerified email at uow.edu.au
