Application of"Artificial+Intelligence"Compound Regression Management Method in Blast Furnace Production
ZHAO Lihua
WANG Zhigang
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.
Keywords：blast furnace melted ironsilica contentcompound regressionkey parametersprediction accuracy
Publication Date：2024-08-20
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：4( 54-56,60 )