首页|基于GA-BP神经网络的多无人艇协同作战效能评估

基于GA-BP神经网络的多无人艇协同作战效能评估

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在现代化海战中,多无人艇协同作战作为新的作战形式,对其作战效能进行科学准确的评估十分重要.针对多无人艇系统协同作战的特点,结合ADC方法和OODA决策链建立协同作战效能评估指标体系.考虑传统评估方法具有过于依赖专家经验的缺点,引入BP神经网络构建多无人艇协同作战评估模型,利用遗传算法(GA)对神经网络进行全局优化并对模型进行仿真验证.结果表明,该模型可有效地对多无人艇系统协同作战效能进行评估.
Effectiveness evaluation for multiple unmanned surface vehicles cooperative combat based on GA-BP neural network
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.

multiple unmanned surface vehicles systemcombat effectiveness evaluationindex systemneural net-work

王翀、倪海参、王赢旋、黄炳涛

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中国舰船研究院,北京 100101

哈尔滨工程大学船舶工程学院,黑龙江哈尔滨 150001

多无人艇系统 作战效能评估 指标体系 神经网络

2024

舰船科学技术
中国舰船研究院,中国船舶信息中心

舰船科学技术

CSTPCD北大核心
影响因子:0.373
ISSN:1672-7649
年,卷(期):2024.46(1)
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