随着现代战争智能化、信息化、体系化程度提升，对未来作战提出了作战效能实时评估和方案高效决策的需求。针对有人/无人机协同空面作战效能评估问题，提出基于作战仿真推演和人工神经网络的智能评估方法。依托仿真推演平台，通过构建作战效能评估指标体系、设计作战推演流程、综合评估结果，获取推演评估数据，运用BP神经网络对数据进行训练并检验训练效果，最用进行实例分析验证方法可行性，并通过灵敏度分析研究各方案关键指标及其影响。本文方法可为有人/无人机协同作战效能评估、装备研究改进以及作战方案快速决策提供技术参考。
With the increasing intelligence, informatization, and systematization of modern warfare, there emerges a demand for real-time combat effectiveness evaluation and efficient decision-making in future operations. To address the effectiveness evaluation problem in manned aerial vehicle(MAV)/unmanned aerial vehicle(UAV) cooperative air-to-ground combat, this paper proposes an intelligent assessment method based on combat simulation deduction and artificial neural networks. Supported by the simulation deduction system, evaluation data are obtained through constructing an combat effectiveness evaluation index system, designing simulation deduction processes, and synthesizing evaluation results. BP neural network is employed to train the data and verify training effectiveness. Case analysis validates the feasibility of the method, while sensitivity analysis investigates key indicators of various schemes and their impacts. The proposed method provides technical references for effectiveness evaluation of MAV/UAV cooperative combat, equipment improvement research, and rapid operational decision-making.
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