A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting

A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting

To address the issues of slow convergence and large errors in existing metaheuristic algorithms when optimizing neural network-based subway passenger flow prediction, we propose the following improvements. First, we replace the random initialization method of the population in the SSA with Circle ma...

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Bibliographic Details
Main Authors: Jing Liu, Qingling He, Zhikun Yue, Yulong Pei
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Mathematics
Subjects:
urban transit
metro station passenger flow forecasting
improved sparrow search algorithm
convolutional neural networks
long short-term neural networks
Online Access:https://www.mdpi.com/2227-7390/12/24/3929
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