Hardenability Prediction of Gear Steel in Refining Process

摘要：

Hardenability prediction is very difficult in the steel refining process. Based on the idea that the accuracy of model can be significantly improved by combining several sub-models, a multiple support vector machine(MSVM) based hardenability prediction model is proposed in this paper. The influence factors of hardenability are analysised to determines the number of sub-model and the input variables of the sub-model. In order to improve the precision and generalization capability of the prediction model, genetic algorithm (GA) is adopted to optimize the parameters of MSVM. The simulation results demonstrate the efficiency of the method.

关键词： hardenability prediction support vector machines genetic algorithm gear steel

作者: LIN Ping WANG Fu-li LIU Liu

作者单位: Key Laboratory of Integrated Automation of Process Industry, Ministry of Education, Northeastern Uni Key Laboratory of Integrated Automation of Process Industry, Ministry of Education, Northeastern Uni Metallurgical Department ,General Iron&Steel Research Institute , Beijing 100081

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 6183-6189

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）