| Long short-term memory neural network for traffic speed prediction using remote microwave sensor data X Ma, Z Tao, Y Wang, H Yu, Y Wang Transportation Research Part C: Emerging Technologies 54, 187-197, 2015 | 2328 | 2015 |
| Learning traffic as images: A deep convolutional neural network for large-scale transportation network speed prediction X Ma, Z Dai, Z He, J Ma, Y Wang, Y Wang sensors 17 (4), 818, 2017 | 1552 | 2017 |
| Mining Smart Card Data for Transit Riders' Travel Patterns X Ma, YJ Wu, Y Wang, F Chen, J Liu Transportation Research Part C: Emerging Technologies 36, 1-12, 2013 | 792 | 2013 |
| Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks H Yu, Z Wu, S Wang, Y Wang, X Ma Sensors 17 (7), 1501, 2017 | 694 | 2017 |
| Large-scale transportation network congestion evolution prediction using deep learning theory X Ma, H Yu, Y Wang, Y Wang PloS one 10 (3), e0119044, 2015 | 614 | 2015 |
| Understanding commuting patterns using transit smart card data X Ma, C Liu, H Wen, Y Wang, YJ Wu Journal of Transport Geography 58, 135-145, 2017 | 397 | 2017 |
| A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership X Ma, J Zhang, C Ding, Y Wang Computers, Environment and Urban Systems 70, 113-124, 2018 | 281 | 2018 |
| Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks Y Li, X Wang, S Sun, X Ma, G Lu Transportation Research Part C: Emerging Technologies 77, 306-328, 2017 | 259 | 2017 |
| Prioritizing influential factors for freeway incident clearance time prediction using the gradient boosting decision trees method X Ma, C Ding, S Luan, Y Wang, Y Wang IEEE Transactions on Intelligent Transportation Systems 18 (9), 2303-2310, 2017 | 253 | 2017 |
| Predicting short-term subway ridership and prioritizing its influential factors using gradient boosting decision trees C Ding, D Wang, X Ma, H Li Sustainability 8 (11), 1100, 2016 | 202 | 2016 |
| Parallel architecture of convolutional bi-directional LSTM neural networks for network-wide metro ridership prediction X Ma, J Zhang, B Du, C Ding, L Sun IEEE Transactions on Intelligent Transportation Systems 20 (6), 2278-2288, 2018 | 195 | 2018 |
| Profit distribution in collaborative multiple centers vehicle routing problem Y Wang, X Ma, Z Li, Y Liu, M Xu, Y Wang Journal of cleaner production 144, 203-219, 2017 | 188 | 2017 |
| Learning dynamic and hierarchical traffic spatiotemporal features with transformer H Yan, X Ma, Z Pu IEEE Transactions on Intelligent Transportation Systems 23 (11), 22386-22399, 2021 | 185 | 2021 |
| Two-echelon location-routing optimization with time windows based on customer clustering Y Wang, K Assogba, Y Liu, X Ma, M Xu, Y Wang Expert Systems with Applications 104, 244-260, 2018 | 159 | 2018 |
| Forecasting transportation network speed using deep capsule networks with nested LSTM models X Ma, H Zhong, Y Li, J Ma, Z Cui, Y Wang IEEE Transactions on Intelligent Transportation Systems 22 (8), 4813-4824, 2020 | 149 | 2020 |
| A fuzzy-based customer clustering approach with hierarchical structure for logistics network optimization Y Wang, X Ma, Y Lao, Y Wang Expert systems with applications 41 (2), 521-534, 2014 | 140 | 2014 |
| Impacts of free-floating bikesharing system on public transit ridership X Ma, X Zhang, X Li, X Wang, X Zhao Transportation research part D: transport and environment 76, 100-110, 2019 | 137 | 2019 |
| Sustainable station-level planning: An integrated transport and land use design model for transit-oriented development X Ma, X Chen, X Li, C Ding, Y Wang Journal of Cleaner Production 170, 1052-1063, 2018 | 133 | 2018 |
| Learning traffic as a graph: A gated graph wavelet recurrent neural network for network-scale traffic prediction Z Cui, R Ke, Z Pu, X Ma, Y Wang Transportation Research Part C: Emerging Technologies 115, 102620, 2020 | 124 | 2020 |
| Cooperation and profit allocation in two-echelon logistics joint distribution network optimization Y Wang, X Ma, M Liu, K Gong, Y Liu, M Xu, Y Wang Applied Soft Computing 56, 143-157, 2017 | 124 | 2017 |
Yinhai WangProfessor of Civil and Environmental Engineering, University of WashingtonVerified email at uw.edu
