In modern naval combat,as a new form of combat,it is very important to evaluate the combat effectiveness scientifically and accurately.According to the characteristics of multiple Unmanned Surface Vehicles system cooperative combat,the effectiveness evaluation index system is established by combining ADC method and OODA decision chain.Considering the shortcomings of traditional evaluation methods that rely too much on expert experience,BP neural network is introduced to build the evaluation model of multiple Unmanned Surface Vehicles cooperative combat.Genetic algorithm is used to optimize the neural network globally,and an example is used to verify the model.The simulation results show that the model can effectively evaluate the cooperative combat effectiveness of multiple Unmanned Surface Vehicles system.
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