| 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 | 112 | 2020 |
| OORNet: A deep learning model for on-board condition monitoring and fault diagnosis of out-of-round wheels of high-speed trains Y Ye, B Zhu, P Huang, B Peng Measurement 199, 111268, 2022 | 109 | 2022 |
| 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 | 81 | 2019 |
| 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 | 79 | 2020 |
| 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 | 76 | 2017 |
| 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 | 61 | 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 | 55 | 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 | 51 | 2020 |
| Deep learning-based fault diagnostic network of high-speed train secondary suspension systems for immunity to track irregularities and wheel wear Y Ye, P Huang, Y Zhang Railway Engineering Science, 1-21, 2022 | 50 | 2022 |
| MBSNet: A deep learning model for multibody dynamics simulation and its application to a vehicle-track system Y Ye, P Huang, Y Sun, D Shi Mechanical Systems and Signal Processing 157, 107716, 2021 | 48 | 2021 |
| 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 | 46 | 2021 |
| 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 | 42 | 2019 |
| 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 | 41 | 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 | 39 | 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 | 35 | 2018 |
| 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 (1), 8639589, 2019 | 33 | 2019 |
| Enhancing the understanding of train delays with delay evolution pattern discovery: A clustering and Bayesian network approach P Huang, T Spanninger, F Corman IEEE Transactions on Intelligent Transportation Systems 23 (9), 15367-15381, 2022 | 30 | 2022 |
| 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 | 27 | 2022 |
| 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 | 25 | 2017 |
| 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 | 18 | 2019 |
Chao WenSouthwest Jiaotong University, University of Waterloo, CN RailBestätigte E-Mail-Adresse bei swjtu.cn