Three Revised Kalman Filtering Models for Short-Term Rail Transit Passenger Flow Prediction
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DOI: 10.1155/2016/9717582
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Cited by:
- Fenling Feng & Zhaohui Zou & Chengguang Liu & Qianran Zhou & Chang Liu, 2023. "Forecast of Short-Term Passenger Flow in Multi-Level Rail Transit Network Based on a Multi-Task Learning Model," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
- Yang, Xin & Xue, Qiuchi & Ding, Meiling & Wu, Jianjun & Gao, Ziyou, 2021. "Short-term prediction of passenger volume for urban rail systems: A deep learning approach based on smart-card data," International Journal of Production Economics, Elsevier, vol. 231(C).
- Sun, He, 2023. "Deep Learning and Bayesian Calibration Approach to Hourly Passenger Occupancy Prediction in Beijing Metro: A Study Exploiting Cellular Data and Metro Conditions," DES - Working Papers. Statistics and Econometrics. WS 38783, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Zhang, Qian & Liu, Xiaoxiao & Spurgeon, Sarah & Yu, Dingli, 2021. "A two-layer modelling framework for predicting passenger flow on trains: A case study of London underground trains," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 119-139.
- Lu Zeng & Zinuo Li & Jie Yang & Xinyue Xu, 2022. "CEEMDAN-IPSO-LSTM: A Novel Model for Short-Term Passenger Flow Prediction in Urban Rail Transit Systems," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
- Xianwang Li & Zhongxiang Huang & Saihu Liu & Jinxin Wu & Yuxiang Zhang, 2023. "Short-Term Subway Passenger Flow Prediction Based on Time Series Adaptive Decomposition and Multi-Model Combination (IVMD-SE-MSSA)," Sustainability, MDPI, vol. 15(10), pages 1-30, May.
- Li, Peng & Wu, Weitiao & Pei, Xiangjing, 2023. "A separate modelling approach for short-term bus passenger flow prediction based on behavioural patterns: A hybrid decision tree method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
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