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Journal of Applied Sciences
  Year: 2013 | Volume: 13 | Issue: 9 | Page No.: 1499-1503
DOI: 10.3923/jas.2013.1499.1503
 
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Dynamic Merge Clustering Algorithm and its Application in Evaluation of the Regional Scientific and Technological Innovation Capability
Huang Zhong-Dong and Tian Xue-Mei

Abstract:
Cluster analysis is an important part of study and application in data mining and hierarchical clustering is currently the most widely used clustering method. A dynamic clustering algorithm named DCMA was proposed based on the defects of hierarchical clustering method. The irreversibility and the indispensable process ending condition of specifying the desired number of clusters and threshold adopts clusters diversity to automatically merge and divide the clusters. And clustering analysis and comprehensive evaluation were conducted to test the scientific and technological innovation capacity of 13 prefecture-level cities of Jiangsu Province. Results verified the feasibility and effectiveness of the proposed method. Data processing results show that this method can provide a scientific quantitative decision-making evaluation model for the relevant administrative departments.
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How to cite this article:

Huang Zhong-Dong and Tian Xue-Mei, 2013. Dynamic Merge Clustering Algorithm and its Application in Evaluation of the Regional Scientific and Technological Innovation Capability. Journal of Applied Sciences, 13: 1499-1503.

DOI: 10.3923/jas.2013.1499.1503

URL: https://scialert.net/abstract/?doi=jas.2013.1499.1503

 
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