Research on Short-Term Passenger Flow Prediction of LSTM Rail Transit Based on Wavelet Denoising
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- Aasim, & Singh, S.N. & Mohapatra, Abheejeet, 2019. "Repeated wavelet transform based ARIMA model for very short-term wind speed forecasting," Renewable Energy, Elsevier, vol. 136(C), pages 758-768.
- Tudor Barbu, 2023. "CNN-Based Temporal Video Segmentation Using a Nonlinear Hyperbolic PDE-Based Multi-Scale Analysis," Mathematics, MDPI, vol. 11(1), pages 1-12, January.
- Azam, Muhammad & Khan, Abdul Qayyum & Zafeiriou, Eleni & Arabatzis, Garyfallos, 2016. "Socio-economic determinants of energy consumption: An empirical survey for Greece," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1556-1567.
- Xiao-Qing WANG & Chi-Wei SU & Ran TAO & Oana-Ramona LOBONŢ, 2018. "When will food price bubbles burst? A review," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(12), pages 566-573.
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- Qingliang Zhao & Junji Chen & Xiaobin Feng & Yiduo Wang, 2024. "A Novel Bézier LSTM Model: A Case Study in Corn Analysis," Mathematics, MDPI, vol. 12(15), pages 1-21, July.
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Keywords
rail transit short-term passenger flow prediction; LSTM; wavelet denoising analysis; SVR;All these keywords.
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