{"title":"基于神经网络的气体检测模型实现研究","authors":"Tao Chi, Ming Chen","doi":"10.1109/ICIME.2009.26","DOIUrl":null,"url":null,"abstract":"The conduction route of animal olfactory system has been proposed in this paper. Pattern recognition is considered as the inherent mechanism of the nature and the base of intelligence, which is established on simulation of brain computing pattern. According to this view, the pattern recognition module from computing pattern existing in the olfactory organs to current computer simulation mode inspired by the olfactory organs has been presented in gas inspection device, which mainly based on neutral networks. The module adopts the multi-function sensors array to establish the input layer of neutral networks for online perception. Due to the identification training of neutral networks the identification of qualitative and quantity is finally implemented through the self-learning and analysis.","PeriodicalId":445284,"journal":{"name":"2009 International Conference on Information Management and Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study of Implementing the Model of Gas Inspection Based on Neural Networks\",\"authors\":\"Tao Chi, Ming Chen\",\"doi\":\"10.1109/ICIME.2009.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The conduction route of animal olfactory system has been proposed in this paper. Pattern recognition is considered as the inherent mechanism of the nature and the base of intelligence, which is established on simulation of brain computing pattern. According to this view, the pattern recognition module from computing pattern existing in the olfactory organs to current computer simulation mode inspired by the olfactory organs has been presented in gas inspection device, which mainly based on neutral networks. The module adopts the multi-function sensors array to establish the input layer of neutral networks for online perception. Due to the identification training of neutral networks the identification of qualitative and quantity is finally implemented through the self-learning and analysis.\",\"PeriodicalId\":445284,\"journal\":{\"name\":\"2009 International Conference on Information Management and Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Information Management and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIME.2009.26\",\"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 Information Management and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIME.2009.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study of Implementing the Model of Gas Inspection Based on Neural Networks
The conduction route of animal olfactory system has been proposed in this paper. Pattern recognition is considered as the inherent mechanism of the nature and the base of intelligence, which is established on simulation of brain computing pattern. According to this view, the pattern recognition module from computing pattern existing in the olfactory organs to current computer simulation mode inspired by the olfactory organs has been presented in gas inspection device, which mainly based on neutral networks. The module adopts the multi-function sensors array to establish the input layer of neutral networks for online perception. Due to the identification training of neutral networks the identification of qualitative and quantity is finally implemented through the self-learning and analysis.