{"title":"工业气体传感器行为的人工神经网络建模","authors":"S. Kouda, T. Bendib, S. Barra, A. Dendouga","doi":"10.1109/CCEE.2018.8634510","DOIUrl":null,"url":null,"abstract":"In this paper, we propose the modeling of an industrial gas sensor “MQ-9”, where our modeling is based on ANNs “artificial neural networks The gas sensor model, obtained, operated under a dynamic environment and expresses accurately the MQ-9 gas sensor behavior. Accordingly, it takes into account the nonlinearity and the cross sensitivity in gas selectivity, temperature and humidity. This model is implemented into PSPICE “performance simulation program with integrated circuit emphasis” simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor.","PeriodicalId":200936,"journal":{"name":"2018 International Conference on Communications and Electrical Engineering (ICCEE)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"ANN modeling of an industrial gas sensor behavior\",\"authors\":\"S. Kouda, T. Bendib, S. Barra, A. Dendouga\",\"doi\":\"10.1109/CCEE.2018.8634510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose the modeling of an industrial gas sensor “MQ-9”, where our modeling is based on ANNs “artificial neural networks The gas sensor model, obtained, operated under a dynamic environment and expresses accurately the MQ-9 gas sensor behavior. Accordingly, it takes into account the nonlinearity and the cross sensitivity in gas selectivity, temperature and humidity. This model is implemented into PSPICE “performance simulation program with integrated circuit emphasis” simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor.\",\"PeriodicalId\":200936,\"journal\":{\"name\":\"2018 International Conference on Communications and Electrical Engineering (ICCEE)\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Communications and Electrical Engineering (ICCEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCEE.2018.8634510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Communications and Electrical Engineering (ICCEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCEE.2018.8634510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose the modeling of an industrial gas sensor “MQ-9”, where our modeling is based on ANNs “artificial neural networks The gas sensor model, obtained, operated under a dynamic environment and expresses accurately the MQ-9 gas sensor behavior. Accordingly, it takes into account the nonlinearity and the cross sensitivity in gas selectivity, temperature and humidity. This model is implemented into PSPICE “performance simulation program with integrated circuit emphasis” simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor.