| A hybrid Bayesian network model for predicting delays in train operations J Lessan, L Fu, C Wen Computers & Industrial Engineering 127, 1214-1222, 2019 | 99 | 2019 |
| A deep learning approach for multi-attribute data: A study of train delay prediction in railway systems P Huang, C Wen, L Fu, Q Peng, Y Tang Information Sciences 516, 234-253, 2020 | 94 | 2020 |
| Train dispatching management with data-driven approaches: A comprehensive review and appraisal C Wen, P Huang, Z Li, J Lessan, L Fu, C Jiang, X Xu IEEE Access 7, 114547-114571, 2019 | 72 | 2019 |
| Statistical investigation on train primary delay based on real records: evidence from Wuhan–Guangzhou HSR C Wen, Z Li, J Lessan, L Fu, P Huang, C Jiang International Journal of Rail Transportation 5 (3), 170-189, 2017 | 71 | 2017 |
| Modeling train operation as sequences: A study of delay prediction with operation and weather data P Huang, C Wen, L Fu, J Lessan, C Jiang, Q Peng, X Xu Transportation research part E: logistics and transportation review 141, 102022, 2020 | 64 | 2020 |
| A predictive model of train delays on a railway line C Wen, W Mou, P Huang, Z Li Journal of Forecasting 39 (3), 470-488, 2020 | 54 | 2020 |
| A Bayesian network model to predict the effects of interruptions on train operations P Huang, J Lessan, C Wen, Q Peng, L Fu, L Li, X Xu Transportation Research Part C: Emerging Technologies 114, 338-358, 2020 | 51 | 2020 |
| A hybrid model to improve the train running time prediction ability during high-speed railway disruptions P Huang, C Wen, L Fu, Q Peng, Z Li Safety Science 122, 104510, 2020 | 45 | 2020 |
| Forecasting primary delay recovery of high-speed railway using multiple linear regression, supporting vector machine, artificial neural network, and random forest regression C Jiang, P Huang, J Lessan, L Fu, C Wen Canadian Journal of Civil Engineering 46 (5), 353-363, 2019 | 41 | 2019 |
| Near-term train delay prediction in the Dutch railways network ZC Li, C Wen, R Hu, C Xu, P Huang, X Jiang International Journal of Rail Transportation 9 (6), 520-539, 2021 | 37 | 2021 |
| Statistical delay distribution analysis on high-speed railway trains Y Yang, P Huang, Q Peng, J Li, C Wen Journal of Modern Transportation 27, 188-197, 2019 | 32 | 2019 |
| Stochastic model of train running time and arrival delay: a case study of Wuhan–Guangzhou high-speed rail J Lessan, L Fu, C Wen, P Huang, C Jiang Transportation Research Record 2672 (10), 215-223, 2018 | 32 | 2018 |
| Modeling train timetables as images: A cost-sensitive deep learning framework for delay propagation pattern recognition P Huang, Z Li, C Wen, J Lessan, F Corman, L Fu Expert Systems with Applications 177, 114996, 2021 | 29 | 2021 |
| Modeling the influence of disturbances in high-speed railway systems P Huang, C Wen, Q Peng, C Jiang, Y Yang, Z Fu Journal of advanced transportation 2019, 2019 | 28 | 2019 |
| Data-driven models for predicting delay recovery in high-speed rail C Wen, J Lessan, L Fu, P Huang, C Jiang 2017 4th International Conference on Transportation Information and Safety …, 2017 | 26 | 2017 |
| High-speed railway train timetable conflict prediction based on fuzzy temporal knowledge reasoning H Zhuang, L Feng, C Wen, Q Peng, Q Tang Engineering 2 (3), 366-373, 2016 | 22 | 2016 |
| A study of the minimum safe distance between human driven and driverless cars using safe distance model TH Yimer, C Wen, X Yu, C Jiang arXiv preprint arXiv:2006.07022, 2020 | 21 | 2020 |
| Prediction of train arrival delays considering route conflicts at multi-line stations Z Li, P Huang, C Wen, X Jiang, F Rodrigues Transportation Research Part C: Emerging Technologies 138, 103606, 2022 | 20 | 2022 |
| Comprehensive optimization of a metro timetable considering passenger waiting time and energy efficiency W Li, Q Peng, C Wen, X Xu Ieee Access 7, 160144-160167, 2019 | 20 | 2019 |
| A data-driven time supplements allocation model for train operations on high-speed railways P Huang, C Wen, Q Peng, J Lessan, L Fu, C Jiang International Journal of Rail Transportation 7 (2), 140-157, 2019 | 16 | 2019 |
Ping Huang 黄平Southwest Jiaotong University在 swjtu.edu.cn 的电子邮件经过验证
