| Individual mobility prediction using transit smart card data Z Zhao, HN Koutsopoulos, J Zhao Transportation research part C: emerging technologies 89, 19-34, 2018 | 106 | 2018 |
| Measuring regularity of individual travel patterns G Goulet-Langlois, HN Koutsopoulos, Z Zhao, J Zhao IEEE Transactions on Intelligent Transportation Systems 19 (5), 1583-1592, 2017 | 93 | 2017 |
| Unified estimator for excess journey time under heterogeneous passenger incidence behavior using smartcard data J Zhao, M Frumin, N Wilson, Z Zhao Transportation Research Part C: Emerging Technologies 34, 70-88, 2013 | 59 | 2013 |
| Detecting pattern changes in individual travel behavior: A Bayesian approach Z Zhao, HN Koutsopoulos, J Zhao Transportation research part B: methodological 112, 73-88, 2018 | 53 | 2018 |
| Car pride and its behavioral implications: an exploration in Shanghai Z Zhao, J Zhao Transportation 47 (2), 793-810, 2020 | 46 | 2020 |
| Discovering latent activity patterns from transit smart card data: A spatiotemporal topic model Z Zhao, HN Koutsopoulos, J Zhao Transportation Research Part C: Emerging Technologies 116, 102627, 2020 | 42 | 2020 |
| Memory-augmented dynamic graph convolution networks for traffic data imputation with diverse missing patterns Y Liang, Z Zhao, L Sun Transportation Research Part C: Emerging Technologies 143, 103826, 2022 | 20* | 2022 |
| Individual mobility prediction in mass transit systems using smart card data: An interpretable activity-based hidden Markov approach B Mo, Z Zhao, HN Koutsopoulos, J Zhao IEEE Transactions on Intelligent Transportation Systems 23 (8), 12014-12026, 2021 | 19* | 2021 |
| Joint demand prediction for multimodal systems: A multi-task multi-relational spatiotemporal graph neural network approach Y Liang, G Huang, Z Zhao Transportation Research Part C: Emerging Technologies 140, 103731, 2022 | 16 | 2022 |
| Impact of COVID-19 travel-restriction policies on road traffic accident patterns with emphasis on cyclists: A case study of New York City J Li, Z Zhao Accident Analysis & Prevention 167, 106586, 2022 | 14 | 2022 |
| Combinatorial optimization of construction waste collection and transportation: A case study of Hong Kong W Bi, W Lu, Z Zhao, CJ Webster Resources, Conservation and Recycling 179, 106043, 2022 | 13 | 2022 |
| Car pride: Psychological structure and behavioral implications Z Zhao, J Zhao 94th Annual Meeting of the Transportation Research Board, Washington, DC, 2015 | 13 | 2015 |
| Nettraj: A network-based vehicle trajectory prediction model with directional representation and spatiotemporal attention mechanisms Y Liang, Z Zhao IEEE Transactions on Intelligent Transportation Systems 23 (9), 14470-14481, 2021 | 12* | 2021 |
| Evolution of trip chaining patterns in London from 1991 to 2010 Z Zhao, G Chua, J Zhao Innovations in Travel Modelling Conference, 11, 2012 | 11 | 2012 |
| Individual-level trip detection using sparse call detail record data based on supervised statistical learning Z Zhao, J Zhao, HN Koutsopoulos Transportation Research Board 95th Annual MeetingTransportation Research Board, 2016 | 9 | 2016 |
| Has Transportation Demand of Shanghai, China, Passed Its Peak Growth? Z Zhao, J Zhao, Q Shen Transportation Research Record: Journal of the Transportation Research Board …, 2013 | 7 | 2013 |
| Mobility as a language: Predicting individual mobility in public transportation using n-gram models Z Zhao, HN Koutsopoulos, J Zhao Transportation Research Board 96th Annual MeetingTransportation Research Board, 2017 | 5 | 2017 |
| Automatic Data for Applied Railway Management: Case Study on the London Overground M Frumin, J Zhao, N Wilson, Z Zhao Transportation research record 2353 (1), 47-56, 2013 | 5 | 2013 |
| Bike sharing demand prediction based on knowledge sharing across modes: A graph-based deep learning approach Y Liang, G Huang, Z Zhao 2022 IEEE 25th International Conference on Intelligent Transportation …, 2022 | 4 | 2022 |
| Uncovering spatiotemporal structures from transit smart card data for individual mobility modeling Z Zhao, HN Koutsopoulos, J Zhao Demand for emerging transportation systems, 123-149, 2020 | 4 | 2020 |
Jinhua ZhaoDepartment of Urban Studies and Planning, MIT在 mit.edu 的电子邮件经过验证
