Rotary kiln production process is a complex physical and chemical reaction process, with a large inertia, pure lag and nonlinear characteristics. Complex process, difficult to get a precise mathematical model. In this paper, BP neural network can implement any nonlinear mapping to establish the characteristics of the neural network prediction model, combined with a large cement plant in Guangxi real-time collection of production data, the simulation study. Simulation results show that the model can well predict the temperature of the cement kiln.

BP5.pdf

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