基于相依网络的异质目标智能排序模型

随着战争复杂性的不断提升，目标排序模型必须能够从体系的角度出发，对战场中的异质目标进行综合排序，并满足动态、对抗、可进化的要求.首先基于相依网络理论，从对抗的角度出发，综合考虑敌我双方的能力构建目标体系；然后，提出两阶段的目标排序算法，实现了对作用于不同空间的异质类目标的动态综合排序；最后，设计面向历史对抗数据的目标体系权值调整算法，确保了目标排序模型的适应性.通过在某战役级兵棋系统进行实验并与人类指挥员的经验数据对比，验证了所提出模型的有效性.

The intelligent heterogeneous target ranking model based on interdependent network

As the complexity of war continues to increase, the target ranking model must be able to comprehensively rank heterogeneous targets in the battlefield from a system perspective and meet the requirements of dynamic, confrontational, and evolving. Based on the theory of interdependent network, firstly constructs the target system of system from the perspective of confrontation and considers the capabilities of both the enemy and ourselves. Then, the two-stage target ranking algorithm is proposed to realize the dynamic comprehensive sorting of heterogeneous targets acting on different spaces. Finally, the adjustment algorithm based on historical data is designed to ensure the adaptability of the target ranking model. The effectiveness of the proposed model is verified by experiments in a theater-level wargame system and comparison with the human commanders' empirical data.