Traffic Flow Prediction Based on Multiple Spatio-Temporal Graph Fusion and Dynamic Attention

Accurate traffic flow prediction is a key prerequisite for realizing intelligent transportation systems, and is of great significance for strengthening system simulation and control and improving the decision-making of managers. To address the problem of most existing Graph Convolutional Network (GC...

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Autor principal:	ZHAI Zhipeng, CAO Yang, SHEN Qinqin, SHI Quan
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Editorial Office of Computer Engineering 2025-09-01
coleção:	Jisuanji gongcheng
Assuntos:	intelligent transportation system|traffic flow prediction|spatio-temporal characteristics|graph convolution network (gcn)|multi-head self-attention mechanism
Acesso em linha:	https://www.ecice06.com/fileup/1000-3428/PDF/jsjgc-51-9-139.pdf
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