Based on the skills of initializing the weight distribution and adding an impulse in the neural network, and expanding the ideal of plural weihts, an artificial neural network model with three connection weights between one and another neural unit was established to predict the silicon content of blast furnace hot metal. Ater the neural network was trained in the off-line state on the basis of a large number of practical data of a commercial blast furnace and making many learning patterns, the satisfactory testing and simulating results of the model were obtaines.
展开▼
