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Temperature prediction based on PSO and SVM for Roller hearth Heat Treatment Furnace

In this paper, a new nonlinear system prediction control algorithm is proposed according to the process requirements of Roller-hearth Heat Treatment Furnace. The new control algorithm uses particle swarm optimization (PSO) and support vector machine (SVM) to establish the predictive model. This model is established and simulated using lots of data acquired from the site. The result indicates that this prediction model based on PSO and SVM has can raise the precision of furnace temperature. It is proved that this model has good application future.