Detailed comparison of CNN+LSTM+GNN model performance and resource consumption.

Detailed comparison of CNN+LSTM+GNN model performance and resource consumption.

<p>Detailed comparison of CNN+LSTM+GNN model performance and resource consumption.</p>

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Bibliographic Details
Main Author:	Hao Li (31608) (author)
Other Authors:	Linbing Chen (21238795) (author)
Published:	2025
Subjects:	Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified road network relationships providing robust support offering theoretical support new technical approach experimental results demonstrate complex spatial structure captures temporal dependencies term memory networks graph neural networks intelligent traffic management frequent traffic accidents complex traffic environments trajectories using lstm model &# 8217 innovative combined model traditional prediction methods insufficient prediction accuracy deep learning model traffic networks traditional methods deep learning traffic volume lstm ), xlink "> vehicle speed spatiotemporal features main contributions effectively models economic conditions changing distance
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Summary:	<p>Detailed comparison of CNN+LSTM+GNN model performance and resource consumption.</p>

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