基于BP神经网络的高炉焦比预测方法  

Method to Predict the Coke Rate Based on BP Neural Network

作　　者：范志刚[1] 邱贵宝[1] 贾娟鱼[1] 白晨光[1] 

机构地区：[1]重庆大学材料科学与工程学院,重庆400044

出　　处：《重庆大学学报（自然科学版）》2002年第6期85-87,91,共4页Journal of Chongqing University

摘　　要：焦比是高炉生产过程中的一个重要技术经济指标 ,也是实际生产中需要进行控制的目标之一。因为高炉反应的复杂性 ,采用传统的经验方法对焦比进行预测存在较大的误差。文章采用一个 9-9- 1改进的BP网络对高炉焦比进行预报 ,实验结果证明 ,经过训练的神经网络对高炉焦比有良好的预测效果 ,其预测误差小于 2 %。并根据生产实际探讨了将神经网络和专家系统相结合 。Coke rate is a very important technique index in the processing of metallurgical, and it is also an important goal that should be reached and controlled in practice.The blast furnace is a countercurrent heat and mass exchange reactor involving the solid, liquid and gaseous phases. Using computer encoded mathematical and statistical methods can not get the precise result. An improved 9-9-1 BP(Back propagation) neural network was trained and used in the prediction of the coke rate. The result indicates that the BP nets can predict coke rate accurately and the error between prediction and real coke rate less than 2%. And the use of a hybrid model in actual on-line intelligence control was also discussed.

关 键 词：人工神经网络 焦比 预测 

分 类 号：TF526[冶金工程—钢铁冶金]