摘要
针对制定作战能力评估方案时存在主观性和不确定性的问题,结合专家经验和自学习算法,提出了基于自适应的模糊小波神经网络协同作战能力评估模型。利用小波分析和模糊逻辑理论对神经网络的结构进行优化,同时采用改进的粒子群算法对神经网络的权值进行自适应调节,解决了传统粒子群算法和神经网络易陷入局部极小值、收敛速度慢和抗干扰能力差等问题。最后,通过多架飞机协同作战能力评估相关数据进行训练和验证。仿真试验结果表明,该模型较好地处理了协同作战行动方案的不确定性和复杂性,为指挥决策者提供了有效的作战评估和指挥决策手段。
In order to overcome the subjectivity and uncertainty in developing the engagement capability evaluation scheme,the cooperative engagement capability evaluation model based on adaptive fuzzy wavelt neural network(FWNN)is proposed through expertise and self-learning algorithms.Wavelet analysis and fuzzy logic are used to optimize the structure of neural network(NN),and the weight parameters of NN are adjusted by the improved particle swarm optimization(PSO)algorithm.The problems that the classical PSO and NN algorithms are easy to fall into local minimum point,low convergence speed,bad anti-disturbance,and so on are solved.Finally,the relative cooperative engagement capability indexes of many aircrafts are trained and validated.The simulation results show that the uncertainty and complexity of cooperative engagement schemes are well processed by the proposed model,and valid combat evaluation and command decision strategies for commanders are provided by the model.
作者
王超
马驰
常俊杰
WANG Chao;MA Chi;CHANG Junjie(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1期41-45,共5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
协同作战
小波分析
模糊逻辑
粒子群
神经网络
joint combat
wavelet analysis
fuzzy logic
particle swarm
neural network
