A Time Series Decomposition and Reinforcement Learning Ensemble Method for Short-Term Passenger Flow Prediction in Urban Rail Transit
Abstract Short-term passenger flow prediction (STPFP) helps ease traffic congestion and optimize the allocation of rail transit resources. However, the nonlinear and nonstationary nature of passenger flow time series challenges STPFP. To address this issue, a hybrid model based on time series decomp...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2023-11-01
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Series: | Urban Rail Transit |
Subjects: | |
Online Access: | https://doi.org/10.1007/s40864-023-00205-1 |