R. Parthasarathy, V. Kalaichelvi, Swaminathan H. Sundaram
{"title":"多气体传感器阵列模糊逻辑模型","authors":"R. Parthasarathy, V. Kalaichelvi, Swaminathan H. Sundaram","doi":"10.1109/ICCSP.2015.7322683","DOIUrl":null,"url":null,"abstract":"Gas sensors have the issue of non linearity, low selectivity and cross sensitivity to other gases which cause a huge aberration from the expected results. These can be alleviated if sensors are integrated and studied. While Artificial Neural Network models are not accurate in identification of complex mixtures of gases, this is improved by using a fuzzy logic model for an array of gas sensors which identifies the presence and the concentration of gases efficiently.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A novel fuzzy logic model for multiple gas sensor array\",\"authors\":\"R. Parthasarathy, V. Kalaichelvi, Swaminathan H. Sundaram\",\"doi\":\"10.1109/ICCSP.2015.7322683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Gas sensors have the issue of non linearity, low selectivity and cross sensitivity to other gases which cause a huge aberration from the expected results. These can be alleviated if sensors are integrated and studied. While Artificial Neural Network models are not accurate in identification of complex mixtures of gases, this is improved by using a fuzzy logic model for an array of gas sensors which identifies the presence and the concentration of gases efficiently.\",\"PeriodicalId\":174192,\"journal\":{\"name\":\"2015 International Conference on Communications and Signal Processing (ICCSP)\",\"volume\":\"191 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Communications and Signal Processing (ICCSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSP.2015.7322683\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Communications and Signal Processing (ICCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSP.2015.7322683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel fuzzy logic model for multiple gas sensor array
Gas sensors have the issue of non linearity, low selectivity and cross sensitivity to other gases which cause a huge aberration from the expected results. These can be alleviated if sensors are integrated and studied. While Artificial Neural Network models are not accurate in identification of complex mixtures of gases, this is improved by using a fuzzy logic model for an array of gas sensors which identifies the presence and the concentration of gases efficiently.