Research on deep learning models for traffic flow prediction

HIGHLIGHTS

• What: The model primarily focuses on the spatial features of traffic flow data, neglecting temporal correlations. In the paper, traffic flow data from 8 adjacent time intervals are used as the input for short-term features, and traffic flow data from 7 consecutive days and 2 consecutive weeks are used as the input for long-term features, considering various spatiotemporal features. The Attention mechanism , on the other hand, calculates the correlation weights between nodes, dynamically emphasizing the spatial relationships that are more critical to the prediction results, allowing the model to focus on the more important connection . . .
  

   

  

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