Earticle

초록

영어

Traditional affinity propagation algorithm has inefficient results when conducting clustering analysis of high dimensional data because "dimension effect" lead to difficult find the proper class structure .In view of this, the author proposes an improved algorithm on the basis of Entropy Weight Method and Principal Component Analysis (EWPCA-AP). EWPCA-AP algorithm empowers the sample data by Entropy Weight Method, eliminate data irrelevant attributes by Principal Component Analysis, and travel with neighbor clustering algorithm, realization of high-dimensional data clustering in low dimension space. The numerical result of simulation experiment shows that the new EWPCA-AP algorithm can effectively eliminate the redundancy and irrelevant attributes of data and improve the performance of clustering. In addition, the proposed algorithm is applied in the area of the economy in our country and the clustering result is consistent with the real one. This algorithm provides a new intelligent evaluation method for Chinese economy.

목차

Abstract
 1. Introduction
 2. Affinity Propagation Clustering Algorithm
 3. An Affinity Propagation Algorithm Based on Principal Component Analysis and Entropy Weight Method
  3.1 Entropy Weight Method
  3.2. Principal Component Analysis
  3.3. Affinity Propagation Clustering Algorithm Based on Entropy Weight Methodand Principal Component (EWPCA-AP Clustering Algorithm)
 4. Simulation Experiment and Analysis
  4.1. Silhouette Effective Index
  4.2. Comparison and Analysis
 5. Application of EWPCA-AP Clustering Algorithm in China's Regional Economy
  5.1. Data Selection
  5.2. Clustering Analysis of the Economic Situation of Our China’s Region
 6. Conclusions
 Acknowledgements
 References

키워드

저자

• Wang Limin [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]
• Zhang Li [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]
• Han Xuming [ School of Computer Science and Engineering Changchun University of Technology, Jilin, 130117, China ] Corresponding author
• Ji Qiang [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]
• Mu Guangyu [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]
• Liu Ying [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605