中国机械工程2013，Vol.24Issue(2)：258-263,6.DOI:10.3969/j.issn.1004-132X.2013.02.021
板形模式识别的多输出最小二乘支持向量回归机新方法
A Novel Method for Flatness Pattern Recognition via MLSSVR
摘要
Abstract
In order to overcome the disadvantages that LS-SVR algorithm is not suitable to multiple input multiple output system modeling directly,a novel algorithm defined as MLSSVR was proposed by adding sample absolute errors in objective function. And a novel flatness pattern recognition method based on MLSSVR was put forward by applying MLSSVR algorithm on pattern recognition. Then,comparison between the MLSSVR recognition method and the combination method of LS - SVR was conducted, and the recognition ability of MLSSVR recognition model was tested and analyzed. Experimental results demonstrate the validity of the MLSSVR algorithm. The flatness pattern recognition model based on MLSSVR can avoid complex computation of LS-SVR combination method, enhance the recognition speed effectively, and has higher recognition accuracy and good generalization ability.关键词
最小二乘支持向量回归机/多输出最小二乘支持向量回归机/板形/模式识别Key words
least squares support vector regression(LS- SVR) /multi - output least squares support vector regression(MLSSVR) /flatness/pattern recognition分类
矿业与冶金引用本文复制引用
张秀玲,张少宇,赵文保,徐腾..板形模式识别的多输出最小二乘支持向量回归机新方法[J].中国机械工程,2013,24(2):258-263,6.基金项目
国家自然科学基金资助项目(50675186) （50675186）
