{"title":"饮水流数据的大数据清洗方法","authors":"Rong-Li Gai, H. Zhang, D. N. Thanh","doi":"10.1590/1678-4324-2023220365","DOIUrl":null,"url":null,"abstract":": A HA_Cart_AdaBoost model is proposed to clean the data in drinking-water-quality data. First, the data that do not follow the normal distribution are regarded as outliers and eliminated. Next, the optimal control theory of nonlinear partial differential equations (PDEs) is introduced into the cart decision tree","PeriodicalId":9169,"journal":{"name":"Brazilian Archives of Biology and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Big Data Cleaning Method for Drinking-Water Streaming Data\",\"authors\":\"Rong-Li Gai, H. Zhang, D. N. Thanh\",\"doi\":\"10.1590/1678-4324-2023220365\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": A HA_Cart_AdaBoost model is proposed to clean the data in drinking-water-quality data. First, the data that do not follow the normal distribution are regarded as outliers and eliminated. Next, the optimal control theory of nonlinear partial differential equations (PDEs) is introduced into the cart decision tree\",\"PeriodicalId\":9169,\"journal\":{\"name\":\"Brazilian Archives of Biology and Technology\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brazilian Archives of Biology and Technology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1590/1678-4324-2023220365\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brazilian Archives of Biology and Technology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1590/1678-4324-2023220365","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOLOGY","Score":null,"Total":0}
A Big Data Cleaning Method for Drinking-Water Streaming Data
: A HA_Cart_AdaBoost model is proposed to clean the data in drinking-water-quality data. First, the data that do not follow the normal distribution are regarded as outliers and eliminated. Next, the optimal control theory of nonlinear partial differential equations (PDEs) is introduced into the cart decision tree
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