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Hongyu Zheng
Hongyu Zheng
Verifierad e-postadress på u.northwestern.edu - Startsida
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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
7102017
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
1442018
Exploring impacts of on-demand ridesplitting on mobility via real-world ridesourcing data and questionnaires
X Chen, H Zheng, Z Wang, X Chen
Transportation 48, 1541-1561, 2021
962021
Dynamic optimization strategies for on-demand ride services platform: Surge pricing, commission rate, and incentives
XM Chen, H Zheng, J Ke, H Yang
Transportation Research Part B: Methodological 138, 23-45, 2020
872020
Mechanical energy harvesting from road pavements under vehicular load using embedded piezoelectric elements
Y Chen, H Zhang, Y Zhang, C Li, Q Yang, H Zheng, C Lü
Journal of Applied Mechanics 83 (8), 081001, 2016
642016
How does on-demand ridesplitting influence vehicle use and purchase willingness? A case study in Hangzhou, China
H Zheng, X Chen, XM Chen
IEEE Intelligent Transportation Systems Magazine 11 (3), 143-157, 2019
392019
Plunge and rebound of a taxi market through COVID-19 lockdown: Lessons learned from Shenzhen, China
H Zheng, K Zhang, YM Nie
Transportation Research Part A: Policy and Practice 150, 349-366, 2021
252021
Understanding network travel time reliability with on-demand ride service data
XM Chen, X Chen, H Zheng, C Chen
Frontiers of Engineering Management 4 (4), 388-398, 2017
232017
Efficient dispatching for on-demand ride services: Systematic optimization via Monte-Carlo tree search
XM Chen, X Chen, H Zheng, F Xiao
Transportation Research Part C: Emerging Technologies 127, 103156, 2021
142021
The fall and rise of the taxi industry in the COVID-19 pandemic: a case study
H Zheng, K Zhang, YM Nie
Available at SSRN 3674241, 2020
52020
How does on-demand ridesplitting influence vehicle use and ownership? A case study in Hangzhou, China
H Zheng, X Chen, XM Chen
Proc., 97th Annual Meeting of the Transportation Research Board, 2018
52018
How Many Are Too Many? Analyzing Dockless Bike-Sharing Systems with a Parsimonious Model
H Zheng, K Zhang, Y Nie, P Yan, Y Qu
Transportation Science 58 (1), 152-175, 2023
42023
Random forests for freeway short-term traffic speed prediction
H Zheng, X Chen, XM Chen
17th COTA International Conference of Transportation Professionals, 2017
12017
Does dockless bikesharing create a competition for losers?
H Zheng, K Zhang, M Nie
Available at SSRN 4613247, 2023
2023
Exploring On-Demand Ridesplitting Behavior and Impact on Mobility: a Case Study in Hangzhou, China
X Chen, H Zheng, Z Wang, XM Chen
Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018
2018
A spatio-termporal deep learning approach for short-term prediction of passenger demand
J Ke, H Zheng, H Yang, X Chen
Transport and Society-Proceeding of the 22nd International Conference of …, 2017
2017
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Artiklar 1–16