Traffic accident data quality enhancement method based on generative adversarial network

The invention discloses a traffic accident data quality enhancement method based on a generative adversarial network, and the method comprises the steps: S2, carrying out the preprocessing of a traffic accident data set, and obtaining a preprocessed data set; s3, performing data filling on the preprocessed data set by using a generative interpolation network to obtain a filled data set; s4, judging whether the filled data set meets a preset filling effect or not, and if yes, entering S5; otherwise, returning to S3; s5, performing data balancing processing on data with unbalanced categories in the filled data set to obtain a data set after data balancing processing; and S6, judging whether the data balance processing result achieves a balance effect or not, if so, outputting the data balance processing result as a quality enhancement result of the traffic accident data, and if not, taking the balance processing result as a filled data set and returning to S5. According to the invention, the loss phenomenon of