{"title":"基于模糊逻辑的气味/气体定性分类神经网络分类器","authors":"Ravi Kumar, R. R. Das, V. Mishra, R. Dwivedi","doi":"10.1109/ELECTRO.2009.5441140","DOIUrl":null,"url":null,"abstract":"This paper presents a novel approach to odor discrimination using data obtained from the responses of thick film tin oxide sensor array fabricated at our laboratory and employing backpropagation algorithm trained artificial neural network based on fuzzy logic. Fuzzy membership values were used as target vectors to the proposed neural classifier. Three different versions of backpropagation algorithm were used to train the network and their performances have been compared. Superior learning and classification performance was obtained using proposed model trained with TRAINLM version of the backpropagation algorithm.","PeriodicalId":149384,"journal":{"name":"2009 International Conference on Emerging Trends in Electronic and Photonic Devices & Systems","volume":"234 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A fuzzy logic based neural network classifier for qualitative classification of odors/gases\",\"authors\":\"Ravi Kumar, R. R. Das, V. Mishra, R. Dwivedi\",\"doi\":\"10.1109/ELECTRO.2009.5441140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel approach to odor discrimination using data obtained from the responses of thick film tin oxide sensor array fabricated at our laboratory and employing backpropagation algorithm trained artificial neural network based on fuzzy logic. Fuzzy membership values were used as target vectors to the proposed neural classifier. Three different versions of backpropagation algorithm were used to train the network and their performances have been compared. Superior learning and classification performance was obtained using proposed model trained with TRAINLM version of the backpropagation algorithm.\",\"PeriodicalId\":149384,\"journal\":{\"name\":\"2009 International Conference on Emerging Trends in Electronic and Photonic Devices & Systems\",\"volume\":\"234 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Emerging Trends in Electronic and Photonic Devices & Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELECTRO.2009.5441140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Emerging Trends in Electronic and Photonic Devices & Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELECTRO.2009.5441140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fuzzy logic based neural network classifier for qualitative classification of odors/gases
This paper presents a novel approach to odor discrimination using data obtained from the responses of thick film tin oxide sensor array fabricated at our laboratory and employing backpropagation algorithm trained artificial neural network based on fuzzy logic. Fuzzy membership values were used as target vectors to the proposed neural classifier. Three different versions of backpropagation algorithm were used to train the network and their performances have been compared. Superior learning and classification performance was obtained using proposed model trained with TRAINLM version of the backpropagation algorithm.