End-point Static Prediction of Basic Oxygen Furnace (BOF) Steelmaking Based on INPSVR and WOA

Basic oxygen furnace (BOF) steelmaking plays a significant role in steelmaking process. Therefore, it is necessary to study the modeling of BOF steelmaking. In order to realize the end-point prediction of converter steelmaking, improve the yield of target product and realize energy saving and emission reduction, an improved nonparallel support vector regression (INPSVR) algorithm is proposed in this paper. Meanwhile, in order to speed up the modeling, whale optimization algorithm (WOA) is used to optimize the parameters of INPSVR model. This has some guiding significance for small and medium converter enterprises to ensure tapping quality, improve production efficiency and reduce cost. Experiments results show that the proposed prediction model has perfect performance in accuracy and efficiency.