Prediction of Calcium Yield During Calcium Treatment Process Performed in Steelmaking Using Neural Network

The artificial neural network was applied to predict the calcium yield during calcium treatment process. Three types of neural network models were established, and the optimal model was selected. Effects of contents and temperature of the molten steel on the calcium yield were calculated using the optimal model. The currently developed model can be used to improve the calcium yield and the stability of calcium content during the calcium treatment process.