Abstract
A Homotopic BI neural network model is developed by combining the homotopy theory and the BI neural network model, to improve the defects of the steepest gradient descent algorithm itself, such as low speed converging and liable to be trapped in local minimum. The end-point carbon content and temperature of molten steel in BOF smelting process is predicted by the proposed model and the original. Result shows that the precision of new model is improved significantly. The hit rates are increased by about 5% and 10%, and the forecasting residuals have decreased 16.31% and 8.67% than the conventional ones, respectively. Also, the calculation time of the new model is 10% shorter than BI model.
Published Version
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