Prediction of Rolling Force for Hot Strip Rolling Based on RFR

被引:2
|
作者
Ren Yan [1 ]
Su Nan [1 ]
Yang Jing [1 ]
Gao Xiaowen [1 ]
Wang Huimin [1 ]
Yue Meixia [1 ]
Lv Donghao [1 ]
机构
[1] Inner Mongolia Univ Sci & Technol, Baotou 014010, Peoples R China
关键词
Rolling Force Prediction; Local Outlier Factor; Random Forest Regression; Grid search;
D O I
10.1109/CCDC52312.2021.9602823
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the hot strip rolling, rolling force is one of the important factors affecting the shape of steel strip. There are some errors in the mechanism model used to predict the secondary rolling force of hot strip rolling in a steel company. In this paper, in order to improve the setting accuracy of the rolling force in production line, the rolling force prediction based on historical production data is studied in this paper. First, in order to reduce the computational complexity of the model and improve the prediction accuracy, correlation analysis and local outlier factor algorithm are used to preprocess the data. Secondly, a rolling force prediction model based on random forest regression algorithm is proposed in this paper,Experimental results based on actual data show that the proposed method has a better predictive effect.
引用
收藏
页码:624 / 629
页数:6
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