Intersection traffic state identification method based on PSO-ELM algorithm

The invention provides an intersection traffic state identification method based on a PSO-ELM algorithm. The method comprises the following steps: acquiring a historical traffic flow data set of a labeled intersection connection road section; learning the historical traffic flow data set by using an extreme learning machine (ELM) algorithm, optimizing parameters of the ELM by using a particle swarm optimization (PSO) algorithm, setting a fitness function of the PSO as a mean square error (MSE) of an ELM predicted value and an actual value, taking a parameter at the optimal fitness value as a final parameter of the ELM, and taking a final ELM model as an intersection traffic state recognition model; and identifying the traffic state of the intersection to be identified by using the intersection traffic state identification model. According to the method, the PSO-ELM algorithm is applied to the field of traffic state recognition, and the traffic state of the intersection is recognized by using the traffic state