联合火力打击智能优化系统设计与实现  

Design and Implementation of Intelligent Optimization System for Joint Fire Strike

作　　者：常颖[1] 刘轩铭 刘昊 CHANG Ying;LIU Xuan-ming;LIU Hao(Unit 32295 of PLA, Liaoyang 111000;Unit 32113 of PLA, Jiamusi 154000;National Defense University Joint Operations College, Shijiazhuang 050000;Unit 31696 of PLA, Jinzhou 121000, China)

机构地区：[1]中国人民解放军32295部队,辽宁辽阳111000 [2]中国人民解放军32113部队,黑龙江佳木斯154000 [3]国防大学联合作战学院,河北石家庄050000 [4]中国人民解放军31696部队,辽宁锦州121000

出　　处：《指挥控制与仿真》2021年第1期103-112,共10页Command Control & Simulation

摘　　要：从联合火力打击智能优化系统的系统架构分析出发,详细阐述了涉及联合火力打击智能优化的关键技术:战法策略转译算法、对抗推演算法、体系价值评估算法和多智能体协同进化算法,并重点介绍了协同进化算法的设计原理、“协同+竞争”机制构成、智能体内部构造以及变异和优胜劣汰方法,通过系统设计实验内容,分别检验了冗余项、备选任务规划项、歼灭阈值和内外网调节参数等系统内部参数的优化情况,分析了协同进化算法作为智能算法的优势,最后,通过对比算法的结果,证明本系统的有效性和应用性。Based on the analysis of the system architecture of the intelligent optimization system of combined fire strike,the key technologies related to intelligent optimization of joint fire strike are elaborated in detail:task planning translation algorithm,antagonistic deduction algorithm,system value evaluation algorithm and co-evolution algorithm.The design principle of co-evolution algorithm,the structure of"co-evolution+competition"mechanism,the internal structure of the intelligent body,and the methods of mutation and survival of the fittest are emphatically introduced.Then,through the system design experiment,the optimization of system internal parameters such as redundancy,alternative task planning,annihilation threshold and internal and external network adjustment parameters are tested respectively,and the advantages of co-evolution algorithm as an intelligent algorithm are analyzed.Finally,the effectiveness and application of the system are proved by comparing with the comparison algorithm.

关 键 词：联合火力打击 对抗博弈推演 系统设计 战场迷雾 毁伤拟合 

分 类 号：E94[军事]