{"title":"Prediction of diesel generator performance and emissions using minimal sensor data and analysis of advanced machine learning techniques","authors":"Min-Ho Park, Jae-Jung Hur, Won-Ju Lee","doi":"10.1016/j.joes.2023.10.004","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":48514,"journal":{"name":"Journal of Ocean Engineering and Science","volume":null,"pages":null},"PeriodicalIF":13.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ocean Engineering and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.joes.2023.10.004","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MARINE","Score":null,"Total":0}
期刊介绍:
The Journal of Ocean Engineering and Science (JOES) serves as a platform for disseminating original research and advancements in the realm of ocean engineering and science.
JOES encourages the submission of papers covering various aspects of ocean engineering and science.