H. Cai, Lingjuan Kong, Xianting Li, Xiaoliang Shao
{"title":"考虑真实传感器特性的室内多污染源释放时间已知的快速识别模型","authors":"H. Cai, Lingjuan Kong, Xianting Li, Xiaoliang Shao","doi":"10.1109/ICMREE.2013.6893752","DOIUrl":null,"url":null,"abstract":"A theoretical model was presented for quickly identifying multiple indoor constant contaminant sources with known releasing time by considering the sensor thresholds and measurement errors. The model was numerically demonstrated and validated by case studies. The results indicated that the model can potentially be effective with high sensor thresholds and measurement errors. This study will contribute to developing source identification techniques using real sensors.","PeriodicalId":6427,"journal":{"name":"2013 International Conference on Materials for Renewable Energy and Environment","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A fast model to identify multiple indoor contaminant sources with known releasing time by considering real sensor characteristics\",\"authors\":\"H. Cai, Lingjuan Kong, Xianting Li, Xiaoliang Shao\",\"doi\":\"10.1109/ICMREE.2013.6893752\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A theoretical model was presented for quickly identifying multiple indoor constant contaminant sources with known releasing time by considering the sensor thresholds and measurement errors. The model was numerically demonstrated and validated by case studies. The results indicated that the model can potentially be effective with high sensor thresholds and measurement errors. This study will contribute to developing source identification techniques using real sensors.\",\"PeriodicalId\":6427,\"journal\":{\"name\":\"2013 International Conference on Materials for Renewable Energy and Environment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Materials for Renewable Energy and Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMREE.2013.6893752\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Materials for Renewable Energy and Environment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMREE.2013.6893752","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fast model to identify multiple indoor contaminant sources with known releasing time by considering real sensor characteristics
A theoretical model was presented for quickly identifying multiple indoor constant contaminant sources with known releasing time by considering the sensor thresholds and measurement errors. The model was numerically demonstrated and validated by case studies. The results indicated that the model can potentially be effective with high sensor thresholds and measurement errors. This study will contribute to developing source identification techniques using real sensors.
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