The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The con...The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The connecting structure of combat entities in it is of great importance for supporting the normal process of the system. In this paper, we explore the optimizing strategy of the structure of the anti-aircraft network by establishing extra communication channels between the combat entities.Firstly, the thought of combat network model(CNM) is borrowed to model the anti-aircraft system as a heterogeneous network. Secondly, the optimization objectives are determined as the survivability and the accuracy of the system. To specify these objectives, the information chain and accuracy chain are constructed based on CNM. The causal strength(CAST) logic and influence network(IN) are introduced to illustrate the establishment of the accuracy chain. Thirdly, the optimization constraints are discussed and set in three aspects: time, connection feasibility and budget. The time constraint network(TCN) is introduced to construct the timing chain and help to detect the timing consistency. Then, the process of the multi-objective optimization of the structure of the anti-aircraft system is designed.Finally, a simulation is conducted to prove the effectiveness and feasibility of the proposed method. Non-dominated sorting based genetic algorithm-Ⅱ(NSGA2) is used to solve the multiobjective optimization problem and two other algorithms including non-dominated sorting based genetic algorithm-Ⅲ(NSGA3)and strength Pareto evolutionary algorithm-Ⅱ(SPEA2) are employed as comparisons. The deciders and system builders can make the anti-aircraft system improved in the survivability and accuracy in the combat reality.展开更多
提出了用动态影响网(Dynamic Influence Nets,DINs)对指挥控制(Command and Control,C2)组织行动过程(Course of Actions,COA)问题进行建模的方法。该方法通过引入因果强度参数,替代了传统动态贝叶斯网络中的条件概率表。给出了利用因...提出了用动态影响网(Dynamic Influence Nets,DINs)对指挥控制(Command and Control,C2)组织行动过程(Course of Actions,COA)问题进行建模的方法。该方法通过引入因果强度参数,替代了传统动态贝叶斯网络中的条件概率表。给出了利用因果强度参数进行概率传播的具体计算方法。结合一个联合作战的仿真算例,验证了该建模方法的优越性和有效性。展开更多
基金supported by the National Natural Science Foundation of China(72071206).
文摘The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The connecting structure of combat entities in it is of great importance for supporting the normal process of the system. In this paper, we explore the optimizing strategy of the structure of the anti-aircraft network by establishing extra communication channels between the combat entities.Firstly, the thought of combat network model(CNM) is borrowed to model the anti-aircraft system as a heterogeneous network. Secondly, the optimization objectives are determined as the survivability and the accuracy of the system. To specify these objectives, the information chain and accuracy chain are constructed based on CNM. The causal strength(CAST) logic and influence network(IN) are introduced to illustrate the establishment of the accuracy chain. Thirdly, the optimization constraints are discussed and set in three aspects: time, connection feasibility and budget. The time constraint network(TCN) is introduced to construct the timing chain and help to detect the timing consistency. Then, the process of the multi-objective optimization of the structure of the anti-aircraft system is designed.Finally, a simulation is conducted to prove the effectiveness and feasibility of the proposed method. Non-dominated sorting based genetic algorithm-Ⅱ(NSGA2) is used to solve the multiobjective optimization problem and two other algorithms including non-dominated sorting based genetic algorithm-Ⅲ(NSGA3)and strength Pareto evolutionary algorithm-Ⅱ(SPEA2) are employed as comparisons. The deciders and system builders can make the anti-aircraft system improved in the survivability and accuracy in the combat reality.
文摘提出了用动态影响网(Dynamic Influence Nets,DINs)对指挥控制(Command and Control,C2)组织行动过程(Course of Actions,COA)问题进行建模的方法。该方法通过引入因果强度参数,替代了传统动态贝叶斯网络中的条件概率表。给出了利用因果强度参数进行概率传播的具体计算方法。结合一个联合作战的仿真算例,验证了该建模方法的优越性和有效性。
