{"title":"Machine learning methods in civil engineering: a systematic review","authors":"Saidjon Kamolov","doi":"10.56947/amcs.v21.277","DOIUrl":null,"url":null,"abstract":"Machine learning has found applications across a range of commercial enterprises. One of the exciting industries impacted by AI has been civil engineering. The aim of this paper is to review recent developments in AI as they relate to civil engineering. We highlight potential applications as well as the risks.","PeriodicalId":504658,"journal":{"name":"Annals of Mathematics and Computer Science","volume":"88 21","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Mathematics and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56947/amcs.v21.277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Machine learning has found applications across a range of commercial enterprises. One of the exciting industries impacted by AI has been civil engineering. The aim of this paper is to review recent developments in AI as they relate to civil engineering. We highlight potential applications as well as the risks.