TEA-GCN: Transformer-Enhanced Adaptive Graph Convolutional Network for Traffic Flow Forecasting

Traffic flow forecasting is crucial for improving urban traffic management and reducing resource consumption. Accurate traffic conditions prediction requires capturing the complex spatial-temporal dependencies inherent in traffic data. Traditional spatial-temporal graph modeling methods often rely o...

पूर्ण विवरण

ग्रंथसूची विवरण

मुख्य लेखकों:	Xiaxia He, Wenhui Zhang, Xiaoyu Li, Xiaodan Zhang
स्वरूप:	Artigo
भाषा:	Inglês
प्रकाशित:	MDPI AG 2024-11-01
श्रृंखला:	Sensors
विषय:	graph convolutional networks traffic flow forecasting adaptive graph learning
ऑनलाइन पहुंच:	https://www.mdpi.com/1424-8220/24/21/7086
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