Abstract: 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.

Key words: MAV/UAV cooperative combat, simulation deduction, effectiveness evaluation, BP neural network, Sensitivity Analysis