Short-to-medium Term Passenger Flow Forecasting for Metro Stations using a Hybrid Model

@article{Li2018ShorttomediumTP,
  title={Short-to-medium Term Passenger Flow Forecasting for Metro Stations using a Hybrid Model},
  author={Linchao Li and Yonggang Wang and Gang Zhong and Jian Zhang and B. Ran},
  journal={KSCE Journal of Civil Engineering},
  year={2018},
  volume={22},
  pages={1937-1945}
}
Metro passenger flow forecasting is an essential component of intelligent transportation system. To enhance the forecasting accuracy and explainable of traditional models, a hybrid model combining symbolic regression and Autoregressive Integrated Moving Average Model (ARIMA) was proposed in this paper. It can take unique strength of each single model to capture the complexity patterns beneath data structure. Using the real data from Xi’an metro line 1, the performance of the hybrid model was… Expand
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  • Zhipu Xie, Weifeng Lv, Syed Muhammad Asim Ali, Bowen Du, R. Huang
  • Computer Science
  • 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech)
  • 2018
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