Earticle

초록

영어

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 non-linear 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.

목차

Abstract
 1. Introduction
 2. Unascertained Clustering Algorithm
  2.1. Unascertained Means Clustering
  2.2. Instructiveness Acknowledge Acquisition in Means Clustering
  2.3. Basic Uncertainty Membership Degree
  2.4. Uncertain Means Clustering Algorithm
 3. Constructing of Evaluation System for the International Competitiveness of Coal Industry
 4. International Coal Industry Competitiveness Appraisal Based on Unascertained Clustering
 5. Conclusions
 Acknowledgement
 Reference

키워드

저자

• Xiang Chen [ School of architecture, Hebei University of Engineering, Hebei Handan 056038, China ]
• Yang Liu [ The personnel department, Civil aviation university of China, Tianjin 300300, China ]
• Yuxia Liang [ School of architectural engineering, Shijiazhuang vocational college of science and technology, Shijiazhuang 050000, China ]
• Xin Zhao [ China Xinxing Baoxin Construction Corporation, Beijing 100079, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605