Measurement model of social and economic loss of traffic accident based on particle swarm optimization

Aiming at the problems of low optimization accuracy and low efficiency in the existing traffic accident socio-economic loss measurement model, a traffic accident socio-economic loss measurement model based on particle swarm optimization is proposed. Firstly, Markov statistics is used to calculate the socio-economic loss data of traffic accidents to improve the accuracy of measurement results; Then, measure the social and economic loss of traffic accidents, construct the measurement model of social and economic loss of traffic accidents, and count the independent variables and dependent variables through screening technology; Finally, the particle swarm optimization algorithm is used to optimize the model to obtain the optimal solution, and the objective function is introduced to output the results of the model to realize the design of loss measurement model. The experimental results show that the accuracy of the model optimization method in this paper is not less than 90%.