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

被引：0
|
作者：
Liu, Liming [1 ]
Li, Ping [1 ]
Chu, Maoxiang [1 ]
机构：
[1] Univ Sci & Technol Liaoning, Sch Elect & Informat Engn, Anshan 114051, Peoples R China
来源：
PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年
基金：
中国国家自然科学基金;
关键词：
BOF steelmaking; End-point prediction; Nonparallel support vector regression; WOA algorithm; MODEL;
D O I：
10.1109/CCDC52312.2021.9601393
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：7493 / 7498
页数：6
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