{"title":"基于机器学习的铝合金搅拌摩擦焊特性分析","authors":"Chanjuan Chen","doi":"10.1080/01694243.2024.2345163","DOIUrl":null,"url":null,"abstract":"This research presents a machine learning (ML) approach that integrates Bayesian theorem to predict residual stress, plastic deformation, and peak temperature in friction stir welding (FSW) of diff...","PeriodicalId":14789,"journal":{"name":"Journal of Adhesion Science and Technology","volume":"53 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine learning-based characterization of friction stir welding in aluminum alloys\",\"authors\":\"Chanjuan Chen\",\"doi\":\"10.1080/01694243.2024.2345163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research presents a machine learning (ML) approach that integrates Bayesian theorem to predict residual stress, plastic deformation, and peak temperature in friction stir welding (FSW) of diff...\",\"PeriodicalId\":14789,\"journal\":{\"name\":\"Journal of Adhesion Science and Technology\",\"volume\":\"53 1\",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Adhesion Science and Technology\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1080/01694243.2024.2345163\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Adhesion Science and Technology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1080/01694243.2024.2345163","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Machine learning-based characterization of friction stir welding in aluminum alloys
This research presents a machine learning (ML) approach that integrates Bayesian theorem to predict residual stress, plastic deformation, and peak temperature in friction stir welding (FSW) of diff...
期刊介绍:
Journal of Adhesion Science and Technology ( JAST) provides a forum for the basic and applied aspects of adhesion, chemistry of adhesives, coatings and sealants, and structure-properties relationships in adhesive joints and deals with applications of adhesion principles in all areas of technology.