摘要
针对陆军指挥信息系统效能评估存在的不确定性和主观性等问题,提出了基于自适应小波神经网络(WNN)的指挥信息系统作战效能评估方法。首先,研究了陆军指挥信息系统的主要组成,构建了陆军指挥信息系统三级能力指标体系;然后,基于WNN设计了作战效能评估模型,采用粒子群优化算法和变结构算法分别对小波神经网络的参数和结构进行动态调整,以避免传统神经网络收敛速度慢和易陷入局部最优等问题;最后,进行了收敛性分析和训练评估验证等仿真试验。仿真试验表明,该方法能够高效评估陆军指挥信息系统作战效能,可为快速制定信息系统综合集成和作战应用方案提供理论支撑。
Aiming at the uncertainty and subjectivity of combat effectiveness evaluation of the army command information system(ACIS),the combat effectiveness evaluation model based on the adaptive wavelet neural network(WNN)is proposed.Firstly,the main system composition of ACIS is studied,and the three-level capability index of ACIS is constructed.Then,the combat effectiveness evaluation model based on the adaptive WNN model is designed,and the particle swarm optimization(PSO)algorithm and the variable structure(VS)algorithm are applied to optimize the structure and weight parameters of WNN,to avoid being trapped into the local minimum point,low convergence speed,etc.Finally,the convergence analysis and the simulation verification experiments are carried out.The simulation results show that the proposed model can be applied to evaluate the combat effectiveness of the ACIS effectively,and can provide theoretical support for the rapid development of the information system integration and combat application schemes.
作者
马驰
王超
姜清涛
陈忠
MA Chi;WANG Chao;JIANG Qingtao;CHEN Zhong(The 28th Research Institute of China Electronics Technology Group Corporation,Nanjing 210007,China)
出处
《指挥信息系统与技术》
2020年第5期94-99,共6页
Command Information System and Technology
基金
装备发展部“十三五”装备预研课题
陆军装备部装备预研课题资助项目
关键词
粒子群优化算法
小波神经网络
陆军指挥信息系统
作战效能评估
particle swarm optimization algorithm
wavelet neural network
army command information system
combat effectiveness evaluation
