基于粗糙集理论的电力企业高风险管理模型

Li Zhiyao, Wang Moyu, Ma Xinke, Shen Xiaoliu
{"title":"基于粗糙集理论的电力企业高风险管理模型","authors":"Li Zhiyao,&nbsp;Wang Moyu,&nbsp;Ma Xinke,&nbsp;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,&nbsp;Wang Moyu,&nbsp;Ma Xinke,&nbsp;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}
引用次数: 6

摘要

针对传统的风险管理模型不能有效地处理历史数据的问题,本文提出了一种基于粗糙集理论的高风险客户管理模型。本文简要分析了粗糙集的特点和应用,给出了一种在生成规则之前减少不相关指标的方法。该方法利用了粗糙集在处理大规模数据方面的优势。该模型结合了工程风险管理理论和粗糙集理论,很好地处理了历史数据。最后通过一个实验来说明该模型的建立和应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信