Qualitative and Quantitative Analysis of Multi-gas Based on SVM

摘要：

In order to reduce the errors of electronic nose for multi-gas qualitative and quantitative analysis, this paper used multi-class support vector machine to process the raw data, and compared with the neural network method in the original article. It is indicated that SVM can achieve better prediction accuracy.

关键词： multi-class support vector machine electronic nose quantitative analysis

作者: Jin Cuiyun Cui Yao Wang Ying

作者单位: College of Information Beijing University of Chemical and Technology,Beijing 100029 China

会议类型: 国际会议

会议名称: The Third International Symposium on Test Automation & Instrumentation(第三届国际自动化测试与仪器仪表学术会议 2010 ISTAI)

会议地点: 厦门

会议语种:英文

页码: 965-968

在线出版日期: 2010-05-22（万方平台首次上网日期，不代表论文的发表时间）