GA-BP模型在弹道导弹协同突防效能评估中的应用

Application of GA-BP Model in Ballistic Missile Cooperative Penetration Effectiveness Evaluation

针对弹道导弹协同突防效能评估的问题,采用层次分析法建立弹道导弹协同突防能力评估指标体系,进一步从突防能力与防御能力上建立了攻防体系之间的突防度模型,并给出了基于GA-BP神经网络下的优化权重选取方法。仿真结果表明:GA-BP神经网络与层次分析法和熵权法相比,有着更好的泛化能力,更精确地反映实际作战效能。该方法避免了主观因素的不确定性和事物本身的绝对客观性,利用实时作战数据对弹道导弹协同突防效能进行评估。

Aiming at the problem of evaluating the cooperative penetration efficiency of ballistic missiles,the evaluation index system of ballistic missile cooperative penetration capability is established by analytic hierarchy process(AHP),and the penetration degree model with penetration capability and defense capability is established,a method of optimizing weights based on GA-BP neural network is proposed.Simulation results show that GA-BP neural network has better generalization ability and reflects actual combat effectiveness more accurately,compared with AHP and entropy weight method.This method is used to avoid the uncertainty of subjective factors and the absolute objectivity of things themselves.And the real-time combat data is used to evaluate the cooperative penetration efficiency of the ballistic missiles.