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作 者:黄冬 刘钢 江雪云 刘立志 郭金林[3] HUANG Dong;LIU Gang;JIANG Xueyun;LIU Lizhi;GUO Jinlin(School of Information Science and Engineering,Hunan Institute of Science and Technology,Yueyang 414006,China;Wuhan Institute of Ship Communication,Wuhan 430010,China;College of Systems Engineering,National University of Defense Technology,Changsha 410003,China)
机构地区:[1]湖南理工学院信息科学与工程学院,湖南岳阳414006 [2]武汉船舶通信研究所,湖北武汉430010 [3]国防科技大学系统工程学院,湖南长沙410003
出 处:《系统工程与电子技术》2025年第3期904-911,共8页Systems Engineering and Electronics
基 金:湖南省自然科学基金青年项目(2023JJ40306);湖南省自然科学基金面上项目(2024JJ5173,2024JJ7223);湖南省教育厅科学研究优秀青年项目(20B260,23B0646);湖南省教育厅科学研究重点项目(23A0494)资助课题。
摘 要:为应对现代战争中作战环境的不确定性问题,指挥员需具备实时优化作战行动过程(course of action,COA)的能力和手段,保证态势变化条件下的作战效能。本文考虑作战持续过程中战场态势变化、指挥员意图介入等因素,采用基于贝叶斯网络的行动过程建模,研究反馈机制下的COA实时滚动优化策略,有效提升行动方案的适用性。通过仿真案例分析可知,滚动优化结构所生成的COA方案评价得分能够在单次优化的基础上提高15%以上,表明滚动优化结构的COA实时决策方法,能够克服复杂作战环境下战场态势和指挥员意图的实时变化影响,保证行动方案的全过程持续最优。Because of the uncertainty for the battlefield environment in modern warfare,it is necessary for commanders to obtain the optimal course of action(COA)in real-time and ensure the combat effectiveness under the condition of situation changes.Considering the factors such as the battlefield situation changes and the command intention intervention during the warfare process,by employing Bayesian network model of COA,this paper studies the real-time recursive optimization method of COA under feedback system,which effectively improves the applicability of action scheme.Through the simulation case analysis,it can be seen that the evaluation score of COA scheme generated by recursive optimization structure can be increased by more than 15%on the basis of normal optimization.The result indicates that the influences of battlefield situation changes and the command intention intervention have been overcome by the recursive optimization of COA under complex combat environment,and the optimality has been ensured in the whole combat process.
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