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Aim at the estimation problem of the result values of computer’s overclocking, a solution to optimize LS-SVM regression model is proposed. First the parameter settings and its main results of CPU and graphics card’s overclocking are analyzed, and the deficiency of the commonly used prediction algorithm is discussed, for this the LS-SVM regression model is selected to predict the result’s measurements of overclocking. Then a LCQPSO algorithm is designed to find the optimal values of parameters and the model prediction accuracy and generalization ability is improved. Verified by collect 50 overclocking samples of AMD FX-8350, the prediction error of the algorithm is 80% lower than that of RBF neural network. the results show the effectiveness of the algorithm.