{"title":"RNN视觉分析在火电控制系统辨识中的应用","authors":"L. Ji, Yun Yang, S. Qiu, Yi Wang, Bin Tian","doi":"10.3724/sp.j.1089.2021.19268","DOIUrl":null,"url":null,"abstract":": Due to the problems such as strong continuity and high complexity of the data generated by the thermal power control process, patterns between strong time-dependent real-valued time series and hidden units is proposed. A case study using real power plant data is conducted to verify the effectiveness of iaRNN in assisting users to understand the working mechanism of the model and diagnose model defects.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visual Analytics of RNN for Thermal Power Control System Identification\",\"authors\":\"L. Ji, Yun Yang, S. Qiu, Yi Wang, Bin Tian\",\"doi\":\"10.3724/sp.j.1089.2021.19268\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Due to the problems such as strong continuity and high complexity of the data generated by the thermal power control process, patterns between strong time-dependent real-valued time series and hidden units is proposed. A case study using real power plant data is conducted to verify the effectiveness of iaRNN in assisting users to understand the working mechanism of the model and diagnose model defects.\",\"PeriodicalId\":52442,\"journal\":{\"name\":\"计算机辅助设计与图形学学报\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"计算机辅助设计与图形学学报\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.3724/sp.j.1089.2021.19268\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"计算机辅助设计与图形学学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3724/sp.j.1089.2021.19268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Visual Analytics of RNN for Thermal Power Control System Identification
: Due to the problems such as strong continuity and high complexity of the data generated by the thermal power control process, patterns between strong time-dependent real-valued time series and hidden units is proposed. A case study using real power plant data is conducted to verify the effectiveness of iaRNN in assisting users to understand the working mechanism of the model and diagnose model defects.
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