"人工+智能"复合回归管理方法在高炉生产的应用
Application of"Artificial+Intelligence"Compound Regression Management Method in Blast Furnace Production
赵丽华 1王志刚1
作者信息
- 1. 山东钢铁股份有限公司莱芜分公司,山东 莱芜 271104
- 折叠
摘要
通过归纳一线人工经验,确定关键参数和权重系数,形成"人工+智能"复合最佳回归公式;通过电脑编辑智能程序,实时采集各关键参数,精准预测绩效指标,进而指导实际生产管理.模型铁水硅成分预测准确度90%以上,改进后铁水平均硅降低约0.04%,实现了高炉生产高效运行,经济效益显著.
Abstract
By summarizing the first-line manual experience,determine key parameters and weight coefficients,form the"artificial+intelligence"compound optimal regression formula;by editing smart programs on computers,real-time collection of key parameters,accurately predict performance indicators,and then guide the actual production management.The model can predict the silica content of blast furnace melted iron with more than 90%accuracy.After the model is implemented,the average silica content of blast furnace melted iron is reduced by about 0.04%,and the high efficiency operation of blast furnace is realized with remarkable economic benefits.
关键词
高炉铁水/硅含量/复合回归/关键参数/预测准确度Key words
blast furnace melted iron/silica content/compound regression/key parameters/prediction accuracy引用本文复制引用
出版年
2024
NETL
NSTL
万方数据