{"title":"Embedded system to recognize the heat power of a fuel gas and to classificate the quality of alcohol fuel","authors":"V. Hirayama, F. J. Ramirez-Fernandez","doi":"10.1109/ISIE.2003.1267988","DOIUrl":null,"url":null,"abstract":"This work presents the result obtained to develop an electronic nose to recognize the fuel gas heat power. As a first approach, synthetic data was generated for each sensor. It was considered the use of raw data and the use of a principal component analysis (PCA) to reduce the number of sensors. Two topologies of neural networks have been used, the backpropagation and learning vector quantization (LVQ). A fuzzy inference system (FIS) also has been used as a solution to this problem.","PeriodicalId":166431,"journal":{"name":"2003 IEEE International Symposium on Industrial Electronics ( Cat. No.03TH8692)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 IEEE International Symposium on Industrial Electronics ( Cat. No.03TH8692)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.2003.1267988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This work presents the result obtained to develop an electronic nose to recognize the fuel gas heat power. As a first approach, synthetic data was generated for each sensor. It was considered the use of raw data and the use of a principal component analysis (PCA) to reduce the number of sensors. Two topologies of neural networks have been used, the backpropagation and learning vector quantization (LVQ). A fuzzy inference system (FIS) also has been used as a solution to this problem.
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