{"title":"利用MLP网络对电子舌头的红酒和水读数进行分类","authors":"H. C. D. Sousa, A. Riul","doi":"10.1109/SBRN.2002.1181428","DOIUrl":null,"url":null,"abstract":"Feasible efforts have been made to mimic the human gustatory system through an \"artificial tongue\". This device comprises an array of sensing units that is able to differentiate tastes with a higher sensitivity than the biological system. Experimental results indicate that when the data generated by such sensing units are handled by artificial neural networks, this \"artificial tongue\" can successfully discriminate wines of different winemakers, vintage and grapes, as well as different brands of mineral water, distilled water and Milli-Q water. The accuracy achieved by the experiments suggests that the sensing units may be used to detect abnormal chemical substances in a production line or even set a new approach to control quality standards in food industry.","PeriodicalId":157186,"journal":{"name":"VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Using MLP networks to classify red wines and water readings of an electronic tongue\",\"authors\":\"H. C. D. Sousa, A. Riul\",\"doi\":\"10.1109/SBRN.2002.1181428\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Feasible efforts have been made to mimic the human gustatory system through an \\\"artificial tongue\\\". This device comprises an array of sensing units that is able to differentiate tastes with a higher sensitivity than the biological system. Experimental results indicate that when the data generated by such sensing units are handled by artificial neural networks, this \\\"artificial tongue\\\" can successfully discriminate wines of different winemakers, vintage and grapes, as well as different brands of mineral water, distilled water and Milli-Q water. The accuracy achieved by the experiments suggests that the sensing units may be used to detect abnormal chemical substances in a production line or even set a new approach to control quality standards in food industry.\",\"PeriodicalId\":157186,\"journal\":{\"name\":\"VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings.\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SBRN.2002.1181428\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBRN.2002.1181428","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using MLP networks to classify red wines and water readings of an electronic tongue
Feasible efforts have been made to mimic the human gustatory system through an "artificial tongue". This device comprises an array of sensing units that is able to differentiate tastes with a higher sensitivity than the biological system. Experimental results indicate that when the data generated by such sensing units are handled by artificial neural networks, this "artificial tongue" can successfully discriminate wines of different winemakers, vintage and grapes, as well as different brands of mineral water, distilled water and Milli-Q water. The accuracy achieved by the experiments suggests that the sensing units may be used to detect abnormal chemical substances in a production line or even set a new approach to control quality standards in food industry.