A Time Series Decomposition and Reinforcement Learning Ensemble Method for Short-Term Passenger Flow Prediction in Urban Rail Transit

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...

Full description

Bibliographic Details
Main Authors: Jinxin Wu, Deqiang He, Xianwang Li, Suiqiu He, Qin Li, Chonghui Ren
Format: Article
Language:English
Published: SpringerOpen 2023-11-01
Series:Urban Rail Transit
Subjects:
Variational mode decomposition
Reinforcement learning
Ensemble strategy
Urban rail transit
Short-term passenger flow prediction
Online Access:https://doi.org/10.1007/s40864-023-00205-1

Similar Items

Similar Items