Jintao KE
TitelCiteras avÅr
Deep multi-view spatial-temporal network for taxi demand prediction
H Yao, F Wu, J Ke, X Tang, Y Jia, S Lu, P Gong, J Ye, Z Li
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach
J Ke, H Zheng, H Yang, XM Chen
Transportation Research Part C: Emerging Technologies 85, 591-608, 2017
A simple reservation and allocation model of shared parking lots
C Shao, H Yang, Y Zhang, J Ke
Transportation Research Part C: Emerging Technologies 71, 303-312, 2016
Hexagon-based convolutional neural network for supply-demand forecasting of ride-sourcing services
J Ke, H Yang, H Zheng, X Chen, Y Jia, P Gong, J Ye
IEEE Transactions on Intelligent Transportation Systems 20 (11), 4160-4173, 2018
A universal distribution law of network detour ratios
H Yang, J Ke, J Ye
Transportation Research Part C: Emerging Technologies 96, 22-37, 2018
Ridesourcing car detection by transfer learning
L Wang, X Geng, J Ke, C Peng, X Ma, D Zhang, Q Yang
arXiv preprint arXiv:1705.08409, 2017
Modelling drivers’ working and recharging schedules in a ride-sourcing market with electric vehicles and gasoline vehicles
J Ke, X Cen, H Yang, X Chen, J Ye
Transportation Research Part E: Logistics and Transportation Review 125, 160-180, 2019
Optimizing Online Matching for Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning
J Ke, F Xiao, H Yang, J Ye
arXiv preprint arXiv:1902.06228, 2019
Optimizing matching time interval and matching radius in on-demand ride-sourcing markets
H Yang, X Qin, J Ke, J Ye
Transportation Research Part B: Methodological 131, 84-105, 2020
PCA-based missing information imputation for real-time crash likelihood prediction under imbalanced data
J Ke, S Zhang, H Yang, X Chen
Transportmetrica A: transport science 15 (2), 872-895, 2019
Analysis of multi-modal commute behavior with feeding and competing ridesplitting services
Z Zhu, X Qin, J Ke, Z Zheng, H Yang
Transportation Research Part A: Policy and Practice 132, 713-727, 2020
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network
J Ke, X Qin, H Yang, Z Zheng, Z Zhu, J Ye
arXiv preprint arXiv:1910.09103, 2019
Pricing, Shareability, and Mode Choices in a Ride-Sourcing Market
J Ke, H Yang, X Li, H Wang, J Ye
Available at SSRN 3357362, 2019
Modelling Drivers’ Working and Recharging Schedules in a Ride-sourcing Market
J Ke, X Cen, H Yang, XM Chen
Transportation Research Board 98th Annual MeetingTransportation Research Board, 2019
Modelling and optimizing the real-time matching processes in a ride-sourcing market
H Yang, X Qin, J Ke
Transportation Systems in the Connected Era-Proceedings of the 23rd …, 2018
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Artiklar 1–15