Research on endpoint prediction model of converting furnace
铜转炉吹炼终点预报模型研究*

The endpoint prediction is one of the most important processes of converting furnace. It influences the benefit of the produce directly. The process of converting furnace is completely complex and coupled. To this question, principal component analysis (PCA) method was used to reorganize the factors. On this basis, the genetic algorithm (GA) was introduced by combining Elman neural network to predict the endpoint of converting furnace. The model was set up using MATLAB software. The simulation results show that the model possesses higher precision and practicability.