{"title":"机器学习在材料腐蚀研究中的应用","authors":"Shuaijie Ma, Yanxia Du, Shasha Wang, Yanjing Su","doi":"10.1515/corrrev-2022-0089","DOIUrl":null,"url":null,"abstract":"Abstract The application of machine learning (ML) to corrosion research has become an important trend in corrosion science in recent years. In this paper, the feature extraction method for corrosion data and the ML algorithms commonly used (including artificial neural networks, support vector machines, ensemble learning and other widely used algorithms) in corrosion field is introduced. Then, the characteristics of different algorithms and their application scenarios in the corrosion prediction are summarized. Finally, the development trend of ML in material corrosion field is prospected.","PeriodicalId":10721,"journal":{"name":"Corrosion Reviews","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of machine learning in material corrosion research\",\"authors\":\"Shuaijie Ma, Yanxia Du, Shasha Wang, Yanjing Su\",\"doi\":\"10.1515/corrrev-2022-0089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The application of machine learning (ML) to corrosion research has become an important trend in corrosion science in recent years. In this paper, the feature extraction method for corrosion data and the ML algorithms commonly used (including artificial neural networks, support vector machines, ensemble learning and other widely used algorithms) in corrosion field is introduced. Then, the characteristics of different algorithms and their application scenarios in the corrosion prediction are summarized. Finally, the development trend of ML in material corrosion field is prospected.\",\"PeriodicalId\":10721,\"journal\":{\"name\":\"Corrosion Reviews\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2023-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Corrosion Reviews\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1515/corrrev-2022-0089\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ELECTROCHEMISTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Corrosion Reviews","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1515/corrrev-2022-0089","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ELECTROCHEMISTRY","Score":null,"Total":0}
Application of machine learning in material corrosion research
Abstract The application of machine learning (ML) to corrosion research has become an important trend in corrosion science in recent years. In this paper, the feature extraction method for corrosion data and the ML algorithms commonly used (including artificial neural networks, support vector machines, ensemble learning and other widely used algorithms) in corrosion field is introduced. Then, the characteristics of different algorithms and their application scenarios in the corrosion prediction are summarized. Finally, the development trend of ML in material corrosion field is prospected.
期刊介绍:
Corrosion Reviews is an international bimonthly journal devoted to critical reviews and, to a lesser extent, outstanding original articles that are key to advancing the understanding and application of corrosion science and engineering in the service of society. Papers may be of a theoretical, experimental or practical nature, provided that they make a significant contribution to knowledge in the field.