Application Of SVM Algorithm And Inverse System In Thermai Control System

In this paper,the theory about Support Vector Machine (SVM) and inverse system method is firstly introced.And then,considering the problem of parameter selection of SVM. Particle Swarm Optimization(PSO) algorithm is applied to help to determine parameters of SVM.The sparseness in the training result of support vector machine is introduced as part of fitness function of PSO algorithm.Summation of empirical risk and support vector divided by training set's size is employed as fitness function.In simulation experiment of a non-linear system, modeling result proved that the proposed method overcame overfitting problem in training process and the predict precision of SVM predict model is enhanced. As generalization ability of SVM's trainning result is guaranteed,SVM algorithm was applied in inverse system modeling. The usual SVM inverse system method is detailedly introduced,and the modeling of MIMO nonlinear discrete system'sαth-order inverse was emulated and proved that SVM is just effective for modeling a th-order inverse and help a lot in decoupling the MIMO system.