Nonlinear Compensation of Carrier Catalytic Methane Sensor Based on Least Squares Support Vector Regression

摘要：

Detection Principle of carrier catalytic methane sensor is introduced and the nonlinear problem of the sensor is indicated. In order to enhance the measure precision of the methane sensor, the nonlinear compensation model was set up by adopting Least Squares Support Vector Regression which is an Support Vector Machines version that works with a least squares cost function, Support Vector Machines is powerful for the problem characterized by small sample, nonlinearity, and local minima. The experimental results show that nonlinear problem of the carrier catalytic methane sensor is greatly compensated by adopting the nonlinear compensation model based on of Least Squares Support Vector Regression, and the model is effective.

关键词： carrier catalytic methane sensor Least Squares Support Vector Regression nonlinear compensation

作者: ZHANG Li DANG Nan WANG Rulin WU Jinting

作者单位: Institute of Mechanical Electronic and Information Engineer, China University of Mining and Technology(Beijing),Beijing

会议类型: 国内会议

会议名称: 第四届全国大学生创新年会

会议地点: 上海

会议语种:英文

页码: 315-318

在线出版日期: 2011-10-22（万方平台首次上网日期，不代表论文的发表时间）