Error Correction of Support Vector Regression Model for Copper-Matte Converting Process

摘要：

　　To improve the performance of copper-matte Peirce-Smith Converting(PSC),the influence of local process data to e-support vector regression(SVR)model for converting process is studied.This paper proposes an Error Correction method for e-Support Vector Regression(EC_SVR),in which the influence of local support vector to prediction results is considered.Two EC_SVR models for slag weight and blowing time of S1 period(that is,the first slag producing period of PSC)are developed by the real production data.Simulation results show that EC_SVR model can significantly improve prediction accuracy and generalization of the converting decision variable in S1 period.

关键词： Support vector regression Error correction Copper-matte converting Prediction accuracy Generalization

作者: Jun Chen Xiaoqi Peng Xiuming Tang

作者单位: School of Information Science and Engineering,Central South University,No.932 LuShan Road,Changsha,C School of Information Science and Engineering,Central South University,No.932 LuShan Road,Changsha,C Institute of Information and Electrical Engineering,Hunan University of Science and Technology,Taoyu

会议类型: 国际会议

会议名称: The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)

会议地点: 福州

会议语种:英文

页码: 117-127

在线出版日期: 2015-05-08（万方平台首次上网日期，不代表论文的发表时间）