Gas Quantitative Analysis with Support Vector Machine

摘要：

Gas sensor array is an important part of electronic nose. The gas analysis performance of electronic nose is affected badly by the cross sensitivity of gas sensor array. In order to solve the problem of the cross sensitivity, in this work a new method based on support vector machine (SVM) is used for pattern analysis of gas mixture quantitative analysis. The proposed method has been used for processing the measuring data obtained by a gas mixture experiment of butane and ethanol, in which the sensor array is composed of three sensors. The results clearly show that the SVM is effective technique for gas mixture quantitative analysis. Also, the SVM can achieve better prediction accuracy than BP neural network.

关键词： Quantitative Analysis Gas Mizture Support Vector Machine Electronic Nose

作者: Liang Xie Xiaodong Wang

作者单位: Department of Electronic Engineering,Zhejiang Normal University,Jinhua 321004,China

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: 5148-5151

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）