{"title":"Coal Industry International Competitiveness Research","authors":"Xiang Chen, Y. Liu, Yuxia Liang, Xin Zhao","doi":"10.14257/ASTL.2016.121.40","DOIUrl":null,"url":null,"abstract":"The unascertained clustering is a new clustering method, which combines unascertained theory and clustering theory to construct the unascertained measure, and uses the unascertained measure as set membership to indicate the membership relation between the samples with the different classes. It overcomes the disadvantage of means clustering algorithm, that a sample definitely belongs to a class, which made greater progress than -means clustering. There are complex nonlinear relationship between the coal industry competitiveness and various factors. The article established the evaluation influencing factors system of coal industry international competitiveness. 6 unascertained clustering method to cluster competitiveness. It found out each class center, and gave the membership degree of the samples belong to each class, which better resolved the problem of classifying the coal industry international competitiveness.","PeriodicalId":153703,"journal":{"name":"Advanced Science and Technology Letters","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science and Technology Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14257/ASTL.2016.121.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The unascertained clustering is a new clustering method, which combines unascertained theory and clustering theory to construct the unascertained measure, and uses the unascertained measure as set membership to indicate the membership relation between the samples with the different classes. It overcomes the disadvantage of means clustering algorithm, that a sample definitely belongs to a class, which made greater progress than -means clustering. There are complex nonlinear relationship between the coal industry competitiveness and various factors. The article established the evaluation influencing factors system of coal industry international competitiveness. 6 unascertained clustering method to cluster competitiveness. It found out each class center, and gave the membership degree of the samples belong to each class, which better resolved the problem of classifying the coal industry international competitiveness.