Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model

Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model

Accurate and timely passenger flow prediction is important for the successful deployment of rail transit intelligent operation. The Sparrow Search Algorithm (SSA) has been applied to the parameter optimization of a Long-Short-Term Memory (LSTM) model. To solve the inherent weaknesses of SSA, this pa...

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Bibliographic Details
Main Authors: Xing Zhao, Chenxi Li, Xueting Zou, Xiwang Du, Ahmed Ismail
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Mathematics
Subjects:
passenger flow prediction
long-short-term memory
improved sparrow search algorithm
machining learning
Online Access:https://www.mdpi.com/2227-7390/12/22/3556
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