Driving intention identification method of self-adaptive double particle swarm optimization support vector machine

The invention provides a driving intention identification method of a self-adaptive double particle swarm optimization support vector machine, and relates to the technical field of gear shifting control strategies of an automobile gearbox. Driving intention classification numbering is carried out according to collected data, in order to solve the influence of parameter selection of the support vector machine on the model learning capability, the self-adaptive double particle swarm optimization is utilized for carrying out parameter optimization of the support vector machine, then the optimizedsupport vector machine is trained and verified through a collected data set, and finally, the driving intention is identified through the data acquired in real time. According to the method, the support vector machine in machine learning is adopted, the support vector machine is optimized, and therefore the driving intention can be quickly identified, the identification accuracy is high, the method can be applied to the