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

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.
 

Key words: least squares support vector regression(LS-SVR), multi-output least squares support vector regression(MLSSVR), flatness, pattern recognition