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结合光电干扰武器系统的工作过程,对影响目标威胁评估的各种因素进行了分析,讨论了常用威胁评估方法的缺点和不足,提出了基于神经网络的空中目标的威胁估计算法,利用神经网络良好的自适应能力和自学习能力,通过样本数据训练,确定各个因素之间的非线性复杂关系,并通过示例介绍了目标威胁值的解算过程;与层次分析法进行了比较,结果表明,神经网络可以很好地逼近各个因素之间的权重关系,提高了空中目标威胁估计算法的准确性和适应性。
Combining with the working process of the system, this paper analyzes the various factors affecting the target threat assessment, discusses the shortcomings and deficiencies of the common threat assessment methods, and proposes a threat estimation algorithm based on the neural network, which uses the neural network Adaptive ability and self-learning ability. Through the training of sample data, the non-linear complex relationship among various factors is determined, and the solution process of target threat value is introduced by example. Compared with AHP, the results show that nerve The network can well approximate the weight relationship among various factors and improve the accuracy and adaptability of the air target threat estimation algorithm.