Optimizing Traffic Flow Forecasting Model Based on Spatial-Temporal Analysis

Inhalt:
To optimize the reasonable dispatch of limited highway resources, the accuracy of traffic flow prediction plays an important role in alleviating road congestion. In this paper, the historical traffic flow time series data are deeply mined, divided into three time series data with different space-time attributes, and then the three time granularities are matched in space-time to form a sequence of information with three space-time attributes at the same time. The simulation results show that based on the same model, the divided sequence information has more potential information characteristics than the original sequence under the same capacity, and the performance of the network model can be further enhanced.