基于集成学习的空战作战体系效能评估  

Effectiveness Evaluation of Air Combat System Based on Ensemble Learning

作　　者：王浩宇[1] 陈灯[1] 李磊 冯晨光 李山山 张俊[1] WANG Haoyu;CHEN Deng;LI Lei;FENG Chenguang;LI Shanshan;ZHANG Jun(Hubei Province Key Laboratory of Intelligent Robot,W uhan Institute of Technology,W uhan 430205,China)

机构地区：[1]武汉工程大学智能机器人湖北省重点实验室,武汉430205

出　　处：《火力与指挥控制》2023年第9期82-91,共10页Fire Control & Command Control

基　　金：武汉工程大学第十三届研究生教育创新基金资助项目(CX2021248)。

摘　　要：对作战体系准确的效能评估是作战决策的关键内容。空战作战体系复杂,传统的人工作战效能评估方法存在主观性强、评估效率低的问题,无法满足现代战争的要求。基于自主研发的DoDAF作战体系建模平台,对典型空战作战体系进行建模,构建评估指标体系,采用专家评分作为训练数据,应用集成学习方法评估作战体系效能。以专家经验作为初始数据,应用机器学习方法进行数据分析可缓解主观性问题,获得更加准确的作战效能评估结果。实验结果表明,基于集成学习的空战作战体系效能评估方法具有更高的效率和精度。Accurate effectiveness evaluation of combat system is a key content of combat decision-making.In the complex air combat system,the traditional combat effectiveness evaluation method is subjective and inefficient,unable to meet the requirements of modern warfare.Based on the independent research DoDAF combat system modeling platform,a typical air combat system is modelled,an evaluation index system is bulit,expert scores is adopted as training data,and ensemble learning methods are applied to evaluate the effectiveness of the combat system.The expert experience is used as the initial data,machine learning methods are applied for data analysis to alleviate the problem of subjectivity and to obtain more accurate results for operational effectiveness evaluation.The experimental results show that the effectiveness evaluation method of air combat system based on ensemble learning has higher efficiency and accuracy.

关 键 词：集成学习 DODAF 作战体系 效能评估 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]