Intelligent Forecasting of Sintered Ore’s Chemical Components Based on SVM

作     者：钟珞 王清波 ZHONG Luo,WANG Qingbo,YUAN Jingling (School of Computer Science and Technology,Wuhan University of Technology,Wuhan 430070,China)

作者机构：School of Computer Science and TechnologyWuhan University of Technology 

出 版 物：《Journal of Wuhan University of Technology(Materials Science)》 (武汉理工大学学报（材料科学英文版）)

年 卷 期：2011年第26卷第3期

页      面：583-587页

核心收录：

学科分类：08[工学] 0806[工学-冶金工程] 080601[工学-冶金物理化学] 

基　　金：Supported by Key Science and Technology Project of Wuhan(No. 20106062327) Self-determined and Innovative Research Funds of WUT (No.2010-YB-20) 

主　　题：sintered ore support vector machine intelligent forecasting nonlinear regression optimized control 

摘      要：Using object mathematical model of traditional control theory can not solve the forecasting problem of the chemical components of sintered *** order to control complicated chemical components in the manufacturing process of sintered ore,some key techniques for intelligent forecasting of the chemical components of sintered ore are studied in this paper.A new intelligent forecasting system based on SVM is proposed and *** results show that the accuracy of predictive value of every component is more than 90%.The application of our system in related companies is for more than one year and has shown satisfactory results.