摘要
为了解决防空反导指控网络抗毁性评估这一问题,通过分析防空反导指挥控制作战进程的特点,得出评价防空反导指控网络抗毁性评估指标,进而建立评估指标体系,通过专家打分和量化得到数据,利用BP神经网络具有的非线性映射能力和自适应自学习能力,建立防空反导指控网络抗毁性评估模型,通过对多种BP算法和隐含层个数的比较来选择性能最佳的神经网络,最后通过实例仿真和多种方法对比验证其设计的有效性。
In order to solve the problem of air and missile defense command and control network invulnerability assessment,by analyzing the characteristics of air and missile defense command and control operations,the evaluation index of air and missile defense command and control network is given,and the evaluation index system is established. Experts score and quantify the data,and use the nonlinear mapping ability and self-adaptive self-learning ability of BP neural network to establish an anti-destruition evaluation model of air and missile defense command and control network,through the multiple BP algorithms and the number of hidden layers. Compare and select the best performance neural network,and finally verify the effectiveness of the design through case simulation and multiple methods.
作者
姜浩博
李松
林驰
吕元杰
张杰
JIANG Hao-bo;LI Song;LIN Chi;LYU Yuan-jie;ZHANG Jie(Graduate College,Air Force Engineering University,Xi’an 710051,China;School of Air and Missile Defense,Air Force Engineering University,Xi’an 710051,China)
出处
《火力与指挥控制》
CSCD
北大核心
2019年第8期65-70,76,共7页
Fire Control & Command Control
基金
国家自然科学基金青年科学基金（61703412）
中国博士后科学基金资助项目（2016M602996）
关键词
防空反导指控网络
抗毁性
BP神经网络
评估
air defense and anti-missile command and control network
invulnerability
BP neural network
evaluation
