| Travel mode choice: a data fusion model using machine learning methods and evidence from travel diary survey data X Chang, J Wu, H Liu, X Yan, H Sun, Y Qu Transportmetrica A: Transport Science 15 (2), 1587-1612, 2019 | 47 | 2019 |
| Understanding user’s travel behavior and city region functions from station-free shared bike usage data X Chang, J Wu, Z He, D Li, H Sun, W Wang Transportation research part F: traffic psychology and behaviour 72, 81-95, 2020 | 36 | 2020 |
| Relocating operational and damaged bikes in free-floating systems: A data-driven modeling framework for level of service enhancement X Chang, J Wu, H Sun, GH de Almeida Correia, J Chen Transportation Research Part A: Policy and Practice 153, 235-260, 2021 | 35 | 2021 |
| A cooperative strategy for optimizing vehicle relocations and staff movements in cities where several carsharing companies operate simultaneously X Chang, J Wu, GH de Almeida Correia, H Sun, Z Feng Transportation Research Part E: Logistics and Transportation Review 161, 102711, 2022 | 19 | 2022 |
| Understanding and predicting the short-term passenger flow of station-free shared bikes: A spatiotemporal deep learning approach X Chang, Z Feng, J Wu, H Sun, G Wang, X Bao IEEE Intelligent Transportation Systems Magazine 14 (4), 73-85, 2021 | 11 | 2021 |
| A Smart Predict-then-Optimize method for dynamic green bike relocation in the free-floating system X Chang, J Wu, H Sun, X Yan Transportation Research Part C: Emerging Technologies 153, 104220, 2023 | 6 | 2023 |
| Uncertain demand based integrated optimisation for train timetabling and coupling on the high-speed rail network Z Feng, C Cao, A Mostafizi, H Wang, X Chang International Journal of Production Research 61 (5), 1532-1555, 2023 | 2 | 2023 |
| Addressing COVID-induced changes in spatiotemporal travel mobility and community structure utilizing trip data: An innovative graph-based deep learning approach X Chang, J Wu, J Yu, T Liu, X Yan, DH Lee Transportation research part A: policy and practice 180, 103973, 2024 | 1 | 2024 |
| Ridesplitting demand prediction via spatiotemporal multi-graph convolutional network Y Li, H Sun, Y Lv, X Chang Expert Systems with Applications 247, 123207, 2024 | | 2024 |
| Energy-saving operation in urban rail transit: A deep reinforcement learning approach with speed optimization D Wang, J Wu, Y Wei, X Chang, H Yin Travel Behaviour and Society 36, 100796, 2024 | | 2024 |
| Combining travel behavior in metro passenger flow prediction: A smart explainable Stacking-Catboost algorithm J Yu, X Chang, S Hu, H Yin, J Wu Information Processing & Management 61 (4), 103733, 2024 | | 2024 |
| Exploring the relationship between built environment and bike-sharing demand: Does the trip length matter? F Wang, C Yin, X Chang, DH Lee, Z He arXiv preprint arXiv:2210.13912, 2022 | | 2022 |
| Exploring the Relationship between Built Environment and Bikesharing: Does Trip Length Matter? F Wang, C Yin, X Chang, DH Lee, Z He Available at SSRN 4258158, 0 | | |
