Performance and improvement of deep learning algorithms based on LSTM in traffic flow prediction

Performance and improvement of deep learning algorithms based on LSTM in traffic flow prediction

Abstract Existing traffic flow prediction research lacks adaptability to complex traffic scenarios and has limited prediction accuracy. This paper introduces an improved LSTM (Long Short-Term Memory) algorithm and sliding window technology to improve the accuracy and stability of traffic flow predic...

Full description

Saved in:
Bibliographic Details
Main Authors: Wei Xu, Eric Blancaflor, Mideth Abisado
Format: Article
Language:English
Published: Springer 2025-03-01
Series:Discover Applied Sciences
Subjects:
Traffic flow prediction
City road
Long short-term memory
Bidirectional gated recurrent unit
Hybrid model
LSTM-BiGRU-attention model
Online Access:https://doi.org/10.1007/s42452-025-06702-1
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items