Application of Least Squares Support Vector Machine on Vehicle Recognition

In the paper, a vehicle recognition model based on LSSVM is presented. In the model, the non-sensitive loss function is replaced by quadratic loss function and the inequality constraints are replaced by equality constraints. Consequently, quadratic programming problem is simplified as the problem of solving linear equation groups, and the SVM algorithm is realized by least squares method. It is presented to choose parameter of kernel function by dynamic way, which enhances preciseness rate of recognition. The simulation results show the model has strong nonlinear solution and anti-jamming ability, and can effectively distinguish vehicle type