Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction

Traffic prediction is a core problem in the intelligent transportation system and has broad applications in the transportation management and planning, and the main challenge of this field is how to efficiently explore the spatial and temporal information of traffic data. Recently, various deep lear...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2021-02, Vol.22 (2), p.1138-1149
Hauptverfasser:	Guo, Kan, Hu, Yongli, Qian, Zhen, Liu, Hao, Zhang, Ke, Sun, Yanfeng, Gao, Junbin, Yin, Baocai
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Convolution Graph convolution network Graphical representations Intelligent transportation systems Neural networks recurrent neural network Recurrent neural networks Roads Spatial data Traffic information traffic prediction Training Transportation management Transportation networks
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