This paper proposes a method to fill in the missing traffic data by using multi-source data. Due to the regularity and specificity of traffic data, Gru network is used to capture missing patterns. The processed missing data, mask data and time interval data are input into Gru network for more in-depth information capture. The results of road speed matching for the floating vehicle data on the road in the corresponding period are further studied by Gru network, and the two results are fused to obtain the filling value of missing value.
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