A gray prediction method for economic loss of road traffic accidents based on Logistic model

Accurate economic loss prediction of road traffic accidents can analyze traffic safety problems from a more objective perspective, so as to achieve a reasonable assessment of social and economic losses of traffic accidents. This paper presents a grey prediction method for economic loss of road traffic accidents based on Logistic model. Firstly, the types of economic losses in traffic accidents are analyzed, and the cleaning treatment of traffic accidents is carried out. Secondly, K-Means clustering algorithm is used to cluster data. Finally, the influencing factors of road traffic safety level are extracted based on the logistics model, and the extracted influencing factors are used as the variables of the economic loss prediction method based on the gray model. The economic loss is predicted according to the economic compensation amount of the level standard. The experimental results show that this method can effectively remove the outliers in the traffic accident data, and improve the accuracy of road traffic accident economic loss prediction, and the fitting degree of the prediction results is within 0.05 of the significance level.