scholarly journals Improved K-Means Clustering Algorithm Based on Dynamic Clustering

2020 ◽  
Vol 4 (1) ◽  
pp. 17-26
Author(s):  
Liguo Zheng ◽  
Keyword(s):  
Clustering Algorithm ◽  
Dynamic Clustering

DGFCM: A New Dynamic Clustering Algorithm

2014 ◽  
Vol 556-562 ◽  
pp. 3945-3948
Author(s):  
Xin Qing Geng ◽  
Hong Yan Yang ◽  
Feng Mei Tao
Keyword(s):  
Vector Space ◽  
Fuzzy Clustering ◽  
Clustering Algorithm ◽  
Vector Space Model ◽  
Dynamic Clustering ◽  
Self Organizing Maps ◽  
Space Model ◽  
Fuzzy Clustering Algorithm ◽  
Present Algorithm ◽  
Self Organizing

This paper applies the dynamic self-organizing maps algorithm to determining the number of clustering. The text eigenvector is acquired based on the vector space model (VSM) and TF.IDF method. The number of clustering acquired by the dynamic self-organizing maps. The threshold GT control the network’s growth.Compared to the traditional fuzzy clustering algorithm, the present algorithm possesses higher precision. The example demonstrates the effectiveness of the present algorithm.

A New Dynamic Clustering Algorithm for an Interval Grey Number

2010 ◽  
pp. 47-58
Author(s):  
Shunxiang Wu ◽  
Junjie Yang ◽  
Wenchang Wei ◽  
Lihua Lin ◽  
Zhifeng Luo
Keyword(s):  
Clustering Algorithm ◽  
Dynamic Clustering ◽  
Grey Number

A Dynamic Clustering Algorithm for Cloud Computing

2013 ◽  
Vol 12 (18) ◽  
pp. 4637-4641
Author(s):  
Zhongxue Yang ◽  
Xiaolin Qin ◽  
Wenrui Li ◽  
Yingjie Yang
Keyword(s):  
Cloud Computing ◽  
Clustering Algorithm ◽  
Dynamic Clustering
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