{"title":"功能安全本体中机器学习安全功能的集成","authors":"M. Kieviet, Padma Iyenghar","doi":"10.1109/INDIN51400.2023.10217928","DOIUrl":null,"url":null,"abstract":"Safety awareness is extremely important when Artificial Intelligence (AI)/Machine Learning (ML) is introduced in the functional safety domain. This paper shows a way to bring the characteristics of the ML development process as well as their particular characteristics into a consensus of the engineering process of functional safety and its reliability requirements.","PeriodicalId":174443,"journal":{"name":"2023 IEEE 21st International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integration of Machine Learning Safety Functions in the Ontology of Functional Safety\",\"authors\":\"M. Kieviet, Padma Iyenghar\",\"doi\":\"10.1109/INDIN51400.2023.10217928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Safety awareness is extremely important when Artificial Intelligence (AI)/Machine Learning (ML) is introduced in the functional safety domain. This paper shows a way to bring the characteristics of the ML development process as well as their particular characteristics into a consensus of the engineering process of functional safety and its reliability requirements.\",\"PeriodicalId\":174443,\"journal\":{\"name\":\"2023 IEEE 21st International Conference on Industrial Informatics (INDIN)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 21st International Conference on Industrial Informatics (INDIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIN51400.2023.10217928\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 21st International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN51400.2023.10217928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integration of Machine Learning Safety Functions in the Ontology of Functional Safety
Safety awareness is extremely important when Artificial Intelligence (AI)/Machine Learning (ML) is introduced in the functional safety domain. This paper shows a way to bring the characteristics of the ML development process as well as their particular characteristics into a consensus of the engineering process of functional safety and its reliability requirements.