{"title":"核电厂风险增加因子预测的复杂网络分析方法","authors":"M. Rifi, M. Hibti, R. Kanawati","doi":"10.5220/0006700000230030","DOIUrl":null,"url":null,"abstract":"We explore applying network based metrics to predict safety metrics of components in Nuclear Power Plants (NPP). We first show how to model accident sequences as complex networks, then we conduct a statistical study over the main network metrics to show that these are highly correlated with the RIF (Risk Increase Factor) which is a very popular metric in nuclear safety studies.","PeriodicalId":414016,"journal":{"name":"International Conference on Complex Information Systems","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Complex Network Analysis Approach for Risk Increase Factor Prediction in Nuclear Power Plants\",\"authors\":\"M. Rifi, M. Hibti, R. Kanawati\",\"doi\":\"10.5220/0006700000230030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We explore applying network based metrics to predict safety metrics of components in Nuclear Power Plants (NPP). We first show how to model accident sequences as complex networks, then we conduct a statistical study over the main network metrics to show that these are highly correlated with the RIF (Risk Increase Factor) which is a very popular metric in nuclear safety studies.\",\"PeriodicalId\":414016,\"journal\":{\"name\":\"International Conference on Complex Information Systems\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Complex Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0006700000230030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Complex Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0006700000230030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Complex Network Analysis Approach for Risk Increase Factor Prediction in Nuclear Power Plants
We explore applying network based metrics to predict safety metrics of components in Nuclear Power Plants (NPP). We first show how to model accident sequences as complex networks, then we conduct a statistical study over the main network metrics to show that these are highly correlated with the RIF (Risk Increase Factor) which is a very popular metric in nuclear safety studies.
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