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基于运动参量的战斗实体模糊聚类方法
引用本文:HUANG Xi-ying,康葳,ZHAO Ding-hai.基于运动参量的战斗实体模糊聚类方法[J].装甲兵工程学院学报,2008,22(3).
作者姓名:HUANG Xi-ying  康葳  ZHAO Ding-hai
作者单位:装甲兵工程学院,训练部,北京,100072
摘    要:战场范围扩大、战斗实体位置疏散使得按照位置进行聚类的方法可信性降低。担负同一作战任务的若干战斗实体往往因保持队形的需要而具有相似的运动规律,因此,使用实体位置、速度、加速度等运动参量进行模糊聚类能够克服位置疏散带来的聚类困难。对实体的运动参量进行归一化,建立模糊等价关系矩阵,根据需要选择适当的截集水平进行聚类,得到不同级别建制的聚类结果。经实验数据检验,该方法能够取得满意的聚类效果,辅助各级指挥员对战场态势进行分析和评估。

关 键 词:运动参量  模糊聚类  战场态势

Fuzzy Clustering Method Based on Motorial Parameter of Fighting Entity
HUANG Xi-ying,KANG Wei,ZHAO Ding-hai.Fuzzy Clustering Method Based on Motorial Parameter of Fighting Entity[J].Journal of Armored Force Engineering Institute,2008,22(3).
Authors:HUANG Xi-ying  KANG Wei  ZHAO Ding-hai
Institution:1(1. Department of Equipment Command and Administration; Academy of Armored Force Engineering; Beijing; 100072; China)2. Department of Training; Beijing 100072; China);
Abstract:The creditability of clustering based on position is reduced because of the expanding of battlefield and scattering of fighting entity. The entities, which take on the same mission, always move with similar motorial rules in order to keep their form of team. Thus, clustering based on entity′s motorial parameters, such as position, velocity and acceleration, can solve the problems resulting from position scattering. First of all, normalization on motorial parameters should be preceded. Then the fuzzy equival...
Keywords:motorial parameter  fuzzy clustering  battlefield situation
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