Optimized Selection Method of Air Combat Course of Action under Stochastic Uncertainty  

作　　者：Yun Zhong Jieyong Zhang Peng Sun Lujun Wan Kepeng Wang 

机构地区：[1]Information and Navigation College,Air Force Engineering University,Xi’an,710077,China [2]Equipment Management and Unmanned Aerial Vehicle Engineering College,Air Force Engineering University,Xi’an,710051,China [3]Air Traffic Control and Navigation College,Air Force Engineering University,Xi’an,710051,China [4]Unit 94040 of PLA,Korla,841000,China

出　　处：《Journal of Systems Science and Systems Engineering》2024年第4期494-518,共25页系统科学与系统工程学报（英文版）

基　　金：co-supported by Natural Science Foundation of Shaanxi(2023-JC-QN-0728);Postdoctoral Science Foundation of China(2021M693942)。

摘　　要：Aiming at the design problem of aviation swarm combat course of action(COA),considering the influence of stochastic parameters in the causal relationship model and optimization problem model,according to the dynamic influence net(DIN)theory,stochastic simulation technique,feedforward neural network(FNN)function approximation technique and multi-objective artificial fish school algorithm(MOAFSA),this paper proposed a COA optimized method based on DIN and multi-objective stochastic chance constraint optimization for aviation swarm combat.First,on the basis of establishing the overall framework of the model and defining the elements of causal relationship modeling,the static and dynamic causal relationship modeling and optimization problem modeling were carried out respectively.Second,the probability propagation mechanism of DIN was established,which mainly included two aspects,i.e.,the overall process and the specific algorithm.Then,input and output data were generated based on stochastic simulation.According to these data,FNN was adopted for function approximation,and MOAFSA was adopted for iterative optimization.Finally,the rationality of the model,and the effectiveness and superiority of the algorithm were verified through multiple sets of simulation cases.

关 键 词：Stochastic uncertainty aviation swarm stochastic simulation course of action feedforward neural network multi-objective artificial fish school algorithm 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]