A traffic flow forecasting method based on node vector-generation countermeasure network was proposed.The reconstruction of road network adjacency relationship was realized by Node2vec method,and the deep mining of road network spatial correlation was realized.Based on the residual graph aggregation mechanism,a generator of spatial characteristics of road network data was con-structed,and the future road network traffic flow data was deduced according to some known data in the road network.Seattle Expressway Network Speed Data Set(Seattle)and California Highway Net-work Speed Data Set(PEMS)were used to verify the effectiveness of the model.The results show that the model can maintain robust traffic flow prediction performance under different data missing modes and different data missing rates.
维普
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