{"title":"基于粗糙集理论的电力企业高风险管理模型","authors":"Li Zhiyao, Wang Moyu, Ma Xinke, Shen Xiaoliu","doi":"10.1016/j.sepro.2011.11.009","DOIUrl":null,"url":null,"abstract":"<div><p>The traditional risk management model can’t process historical data efficiently, this paper proposed a high-risk customer management model based on rough set theory to solve this problem. In this paper we briefly analyze the characteristics and application of rough set, and then give a method to reduce the irrelevant indicators before generating rules. This method is based on the advantages of rough set in processing large scale data. The model combines risk management theory in engineering and rough set theory in a very good way to process the historical data. Finally this paper gives an experiment to illustrate how to establish and apply the proposed model.</p></div>","PeriodicalId":101207,"journal":{"name":"Systems Engineering Procedia","volume":"3 ","pages":"Pages 63-68"},"PeriodicalIF":0.0000,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.sepro.2011.11.009","citationCount":"6","resultStr":"{\"title\":\"High Risk Management Model For The Power Enterprise Based on Rough Set Theory\",\"authors\":\"Li Zhiyao, Wang Moyu, Ma Xinke, Shen Xiaoliu\",\"doi\":\"10.1016/j.sepro.2011.11.009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The traditional risk management model can’t process historical data efficiently, this paper proposed a high-risk customer management model based on rough set theory to solve this problem. In this paper we briefly analyze the characteristics and application of rough set, and then give a method to reduce the irrelevant indicators before generating rules. This method is based on the advantages of rough set in processing large scale data. The model combines risk management theory in engineering and rough set theory in a very good way to process the historical data. Finally this paper gives an experiment to illustrate how to establish and apply the proposed model.</p></div>\",\"PeriodicalId\":101207,\"journal\":{\"name\":\"Systems Engineering Procedia\",\"volume\":\"3 \",\"pages\":\"Pages 63-68\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.sepro.2011.11.009\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Systems Engineering Procedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211381911001627\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systems Engineering Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211381911001627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High Risk Management Model For The Power Enterprise Based on Rough Set Theory
The traditional risk management model can’t process historical data efficiently, this paper proposed a high-risk customer management model based on rough set theory to solve this problem. In this paper we briefly analyze the characteristics and application of rough set, and then give a method to reduce the irrelevant indicators before generating rules. This method is based on the advantages of rough set in processing large scale data. The model combines risk management theory in engineering and rough set theory in a very good way to process the historical data. Finally this paper gives an experiment to illustrate how to establish and apply the proposed model.