{"title":"Grey Clustering Analysis Method for Overseas Energy Project Investment Risk Decision","authors":"Liu Ke , Shen Xiaoliu , Tan Zhongfu , Guo Wenyan","doi":"10.1016/j.sepro.2011.11.008","DOIUrl":null,"url":null,"abstract":"<div><p>An intelligent decision-making method has been put forward to deal with overseas project loans decision-making, which is based on grey clustering analysis method. The grey clustering analysis is an algorithm based on the risk classification causes risk index system which clusters risk of harm degree into grey clustering risk index system, and realizes the decision overseas project loans to measure the risk accurately, and also can measure the results as a sample data set clustering analysis to get to the loan plan for clustering center decision model to complete the project implementation plan outside loans. The effectiveness of the method through the contrast experiment has been validated.</p></div>","PeriodicalId":101207,"journal":{"name":"Systems Engineering Procedia","volume":"3 ","pages":"Pages 55-62"},"PeriodicalIF":0.0000,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.sepro.2011.11.008","citationCount":"35","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systems Engineering Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211381911001615","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35
Abstract
An intelligent decision-making method has been put forward to deal with overseas project loans decision-making, which is based on grey clustering analysis method. The grey clustering analysis is an algorithm based on the risk classification causes risk index system which clusters risk of harm degree into grey clustering risk index system, and realizes the decision overseas project loans to measure the risk accurately, and also can measure the results as a sample data set clustering analysis to get to the loan plan for clustering center decision model to complete the project implementation plan outside loans. The effectiveness of the method through the contrast experiment has been validated.