{"title":"基于数据融合和机器学习算法的智能多传感器过程监测数据质量评估","authors":"T. Segreto, R. Teti","doi":"10.1007/s11740-022-01155-6","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":47298,"journal":{"name":"Production Engineering-Research and Development","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Data quality evaluation for smart multi-sensor process monitoring using data fusion and machine learning algorithms\",\"authors\":\"T. Segreto, R. Teti\",\"doi\":\"10.1007/s11740-022-01155-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":47298,\"journal\":{\"name\":\"Production Engineering-Research and Development\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2022-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Production Engineering-Research and Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s11740-022-01155-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production Engineering-Research and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11740-022-01155-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
期刊介绍:
The journal reports peer reviewed results of latest research in industrial engineering, production engineering and industrial organization. The high level and focus on both the scientific as well as the practical impact of the selected papers will bridge the gap between research and successful industrial application. Researchers in production engineering as well as in operation management and supply chain organization will find recent valuable developments. The main topics span from novel production processes via computer aided engineering to process chain and factory management. Frequently published key note papers provide succinct reviews on the recent progress in particular research areas.