{"title":"质量流量计(T,p)-/spl rho/表的建模技术","authors":"Han Jian-guo, Wu You-Hua, Liu Jiu-Xi","doi":"10.1109/SICE.2000.889659","DOIUrl":null,"url":null,"abstract":"A method based on the training technology of a fuzzy inference adaptive artificial neural network and nonlinear least-square (linear in structure) system identification technology for modeling the (T,P)-/spl rho/ table for a mass flow-meter is introduced. The model has several advantages such as saving calculation workload and storage space, having essential filterability. Thus the method is an effective help for the current development of high-degree integration technology of measuring and instrumentation.","PeriodicalId":254956,"journal":{"name":"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling technology for (T,p)-/spl rho/ table in mass flow-meter\",\"authors\":\"Han Jian-guo, Wu You-Hua, Liu Jiu-Xi\",\"doi\":\"10.1109/SICE.2000.889659\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method based on the training technology of a fuzzy inference adaptive artificial neural network and nonlinear least-square (linear in structure) system identification technology for modeling the (T,P)-/spl rho/ table for a mass flow-meter is introduced. The model has several advantages such as saving calculation workload and storage space, having essential filterability. Thus the method is an effective help for the current development of high-degree integration technology of measuring and instrumentation.\",\"PeriodicalId\":254956,\"journal\":{\"name\":\"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SICE.2000.889659\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SICE.2000.889659","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling technology for (T,p)-/spl rho/ table in mass flow-meter
A method based on the training technology of a fuzzy inference adaptive artificial neural network and nonlinear least-square (linear in structure) system identification technology for modeling the (T,P)-/spl rho/ table for a mass flow-meter is introduced. The model has several advantages such as saving calculation workload and storage space, having essential filterability. Thus the method is an effective help for the current development of high-degree integration technology of measuring and instrumentation.
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