Dynamic graph convolutional traffic flow prediction model based on attention and linear layer fusion

Accurate traffic volume prediction is crucial for optimizing the operational efficiency of road networks and alleviating urban traffic congestion. Traditional models rely on predefined static graph structures, making it difficult to capture dynamic spatiotemporal correlations, and single-time-scale...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Wei Hui, Xiao Hongbo, Zou Beiji, Kui Xiaoyan, Xiao Jianhua, He Jiaju, He Niguli
Format:	Artigo
Sprache:	Chinês
Veröffentlicht:	China InfoCom Media Group 2026-01-01
Schriftenreihe:	大数据
Schlagworte:	dynamic time feature extraction with multi head attention mechanism dynamic graph convolution linear layer fusion
Online-Zugang:	http://www.j-bigdataresearch.com.cn/zh/article/doi/10.11959/j.issn.2096-0271.2026015/
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