A hybrid model used to predict flow stress

To improved the prediction accuracy of the flow stress, a hybrid model based on the Hybrid Least Squares Support Vector Machine (HLS-SVM) and Mathematical Models (MM) was proposed. In HLS-SVM model, the optimal parameters of LS-SVM were obtained by self-adaptive Particle Swarm Optimization (PSO)based on Simulated Annealing (SA). Simulation experiment results revealed that this model could correctly recur to the flow stress in the sample data and accurately predict the non-sample data. The efficiency and accuracy of the predicted flow stress achieved by the proposed model were better than the methods used in most literature.