空战决策知识构建方法研究  

Research on the construction method of air combat decision knowledge

作　　者：吕跃[1] 杨爱武 李战武[1] 奚之飞 LYU Yue;YANG Aiwu;LI Zhanwu;XI Zhifei(Air Force Engineering University, Aeronautics Engineering College, Xi’an 710038, China)

机构地区：[1]空军工程大学航空工程学院,陕西西安710038

出　　处：《系统工程与电子技术》2021年第7期1866-1874,共9页Systems Engineering and Electronics

基　　金：空军工程大学校长基金(XZJK2019040)资助课题。

摘　　要：针对战训数据丰富,数据背后空战决策知识贫乏的问题,提出了一种空战决策知识构建方法。首先,根据空战决策影响因素来分析决策知识的生成过程,选择用产生式规则来表示空战决策知识。其次,针对战训数据存在噪声数据干扰以及连续属性数据难以满足数据挖掘算法离散度量要求的问题,应用了k-means聚类算法来检测离群点并使用最小描述长度准则算法将连续属性离散化。最后,基于预处理后数据,采用粗糙集提取空战最小决策规则知识,通过构建模糊逻辑推理系统实现空战决策知识的推理与应用。仿真表明,该方法能够有效地提取空战决策规则知识以及知识的推理与应用。Aiming at the problem of lacking of knowledge about air combat decision-making behind the abundant combat training data,a method for constructing air combat decision-making knowledge is proposed.Firstly,this method analyzes the process of decision-making knowledge based on the influencing factors of air combat decision-making,and chooses to use production rules to represent air combat decision-making knowledge.Secondly,because it is difficult to meet the discrete measurement requirements of data mining algorithms due to the presence of noisy data and attribute data in combat training.The k-means clustering algorithm is applied to detect outliers and the minimum description length principle algorithm discretizes the continuous attributes.Finally,based on the preprocessed data,rough set is used to extract the minimum knowledge of air combat decision rules,and the reasoning and application of air combat decision-making knowledge are realized by building an fuzzy logical inference system.Simulation shows that this method can effectively extract the knowledge of air combat decision rules and the reasoning and application of knowledge.

关 键 词：决策知识 产生式规则 K-MEANS聚类算法 最小描述长度准则 粗糙集模糊逻辑 

分 类 号：V21[航空宇航科学与技术—航空宇航推进理论与工程]