计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 593-597.

• 综合、交叉与应用 • 上一篇    下一篇

聚类分析算法在不确定性决策中的应用

黄海燕1, 刘晓明1, 孙华勇2, 杨志才3   

  1. 陆军工程大学 南京2100071;
    蚌埠汽车士官学校 安徽 蚌埠2330112;
    酒泉卫星发射中心 甘肃 酒泉7327503
  • 出版日期:2019-06-14 发布日期:2019-07-02
  • 通讯作者: 黄海燕(1990-),女,博士生,主要研究方向为决策理论与方法,E-mail:yanyuyiye@sina.com
  • 作者简介:刘晓明(1956-),男,教授,博士生导师,主要研究方向为军事信息学;孙华勇(1987-),男,硕士,助教,主要研究方向为决策理论与方法;杨志才(1990-),男,硕士,助理工程师,主要研究方向为物联网。
  • 基金资助:
    本文受国家自然科学基金项目(61174198)资助。

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

摘要: 为了更快地获取有用的决策信息,结合当下人工智能技术的发展新趋势,基于K-MEANS等聚类分析算法尝试性地对决策信息进行分析聚类。提出决策信息概念模型,以更好地表述决策信息,方便信息分析处理;结合具体数据实例,将聚类算法应用到不确定性决策中,实现对决策信息的分类推荐,方便快速挖掘关键信息,减少决策时间。最后,研究基于聚类分析算法的评价决策方法,提出聚类信息可用性指标,为度量决策信息中的聚类效果提供一种度量标准。

关键词: K-means, 聚类分析算法, 聚类信息可用性指标, 决策信息

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

中图分类号: 

  • C934
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