Predictive model of Mn-Si alloy Smelting Energy Consumption based on Wavelet Neural Network

Daily average output and unit electricity consumption are two important indicators on production of Mn-Si alloy. There exists a serious nonlinear relationship among daily average output and unit electricity consumption and the ferromanganese's grade and furnace average power and the amount of ferrosilicon powder and the amount of coke etc. The predictive model of Mn-Si Alloy Smelting Energy Consumption based on Wavelet Neural Network was put forward, and the research of verifying the model was made by comparing the predictive value with the practical data of a Ferroalloy Company. The results show that the double hit rate for daily average output and unit electricity consumption achieves at above 90%.