Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 593-597.

• Interdiscipline & Application • Previous Articles     Next Articles

Application of Clustering Analysis Algorithm in Uncertainty Decision Making

HUANG Hai-yan1, LIU Xiao-ming1, SUN Hua-yong2, YANG Zhi-cai3   

  1. PLA Army Engineering University,Nanjing 210007,China1;
    Bengbu Automobile NCO Academy,Bengbu,Anhui 233011,China2;
    Jiuquan Satellite Launch Centre,Jiuquan,Gansu 732750,China3
  • Online:2019-06-14 Published:2019-07-02

Abstract: In order to obtain useful decision information more quickly,combined with the development trend of artificial intelligence technology,the clustering analysis algorithm based on K-MEANS is used to analyze the clutering of decision information.The conceptual model about decision information was put forward to better describe the decision information and facilitate the information analysis and processing.Combining the specific data examples,clustering algorithms were applied to uncertainty decision making to achieve the classification of decision information to facilitate the rapid excavation of key information.Finally,the evaluation method based on clustering analysis algorithm was proposed,and the clustering information availability index was defined,which provides a measure for the clustering effect in the decision information.

Key words: Decision information, K-means, Clustering analysis algorithm, Clustering information availability index

CLC Number: 

  • C934
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