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
[1] 刘辰.国务院印发《新一代人工智能发展规划》:构筑我国人工智能发展先发优势[J].中国科技产业,2017(8):78-79.
[2] BILGE G,HEHL-LANGE S,LANGE E.The use of mobile devices in participatory decision-making[C]∥JoDLA-Journal of Digital Landscape Architecture.Istanbul,Turkey,2016:234-242.
[3] 黄海燕.分布式协同指挥控制一致决策关键技术研究[D].南京:解放军理工大学,2015.
[4] 滕东兴,王子璐,杨海燕,等.基于交互式可视组件的分析决策环境研究[J].计算机学报,2011,34(3):555-565.
[5] 滕东兴,曾志荣,杨海燕,等.一种面向关系型数据的可视质量分析方法[J].软件学报,2013,24(4):810-824.
[6] 张红云,刘向东,段晓东,等.数据挖掘中聚类算法比较研究[J].计算机应用与软件,2003,20(2):5-6.
[7] HE R,MCAULEY J.Ups and Downs:Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering[OL].https://core.ac.uk/display/42679064.
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