An Improved Artificial Neural Network Model for Predicting Silicon Content of Blast Furnace Hot Metal

查看全文 作　　者：Bin Yao, Tianjun Yang, Xiaojun Ning (Metallurgy School, University of Science and Technology Beijing, Beijing 100083, China) 出　　处：《International Journal of Minerals,Metallurgy and Materials》索引2000年第14卷第4期,共4页 摘　　要：Based on the skills of initializing weight distribution, adding an impulse in a neural network and expanding the ideal of plural weights, an artificial neural network model with three connection weights between one and another neural unit was established to predict silicon content of blast furnace hot metal. After 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, satisfactory testing and simulating results of the model were obtained. 关 键 词：BLAST FURNACE SILICON content NEURAL network METALLURGY