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

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 n...

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Published inJournal of systems science and systems engineering Vol. 33; no. 4; pp. 494 - 518
Main Authors Zhong, Yun, Zhang, Jieyong, Sun, Peng, Wan, Lujun, Wang, Kepeng
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2024
Springer Nature B.V
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ISSN1004-3756
1861-9576
DOI10.1007/s11518-024-5610-3

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Summary: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.
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ISSN:1004-3756
1861-9576
DOI:10.1007/s11518-024-5610-3