Coke Quality Prediction Based on Blast Furnace Smelting Process Data

Coke is the main material of blast furnace smelting. The quality of coke is directly related to the quality of finished products of blast furnace smelting, and the evaluation of coke quality often depends on the quality of finished products. However, it is impractical to evaluate coke quality based on finished product quality. Therefore, it is of great significance to establish an artificial intelligence model for quality prediction based on the indicators of coke itself. In this paper, starting from the actual production case, taking the indicators of coke as the feature vector and the quality of finished product as the label, different artificial intelligence models are established. These models predict coke quality, and compare and discuss related algorithms, which lays a foundation for further algorithm improvement.