Simulation design of traffic flow prediction based on genetic optimization support vector machine

Short-term traffic flow has nonlinear traffic characteristics, it can well predict the actual traffic flow in practical work and improve the stability of road traffic. However, traditional traffic flow prediction methods are prone to dimensional disasters in the prediction process. Moreover, support vector machine can transform low-dimensional nonlinear problems on the basis of using nonlinear mapping method, so as to get high-dimensional linear problems. Based on this, this paper proposes a traffic flow prediction model based on genetic optimization support vector machine, and uses simulation design to verify the advantages of the model, which shows that the model prediction data has high agreement with the actual data and small experimental error, so it has strong feasibility.