GRU-LSTM model based on the SSA for short-term traffic flow prediction

GRU-LSTM model based on the SSA for short-term traffic flow prediction

The transportation department relies on accurate traffic forecasting for effective decision-making. However, determining relevant parameters for existing traffic flow prediction models poses challenges. To address this issue, this study proposes a hybrid model, sparrow search algorithm-gated recurre...

Full description

Saved in:
Bibliographic Details
Main Authors: Changxi Ma, Xiaoyu Huang, Yongpeng Zhao, Tao Wang, Bo Du
Format: Article
Language:English
Published: Tsinghua University Press 2025-03-01
Series:Journal of Intelligent and Connected Vehicles
Subjects:
traffic flow prediction
hybrid model
sparrow search algorithm (ssa)
long short-term memory (lstm) network
gated recurrent unit (gru)
Online Access:https://www.sciopen.com/article/10.26599/JICV.2024.9210051
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.sciopen.com/article/10.26599/JICV.2024.9210051

Similar Items