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以拦截巡航导弹为例,针对抗击低空目标特点,提出了弹炮结合防空武器系统作战效能评价指标体系,简要分析了指标选取的理由。然后,采用专家打分的方法取得了几组训练样本,并对所构造的三层BP神经网络进行训练,当训练精度达到要求后,再运用BP神经网络对几种典型的弹炮结合防空武器系统对巡航导弹的作战效能进行了评估。结果表明,在选定指标的基础上,用训练好的BP神经网络评估弹炮结合防空武器系统作战效能是合理的,减少了评估中的人为因素,使评估的结果更为可信。研究结果可为在现有武器装备的基础上开发和研制新型弹炮结合防空武器系统提供理论参考。
Taking the interception of cruise missiles as an example, aiming at the characteristics of fighting low-altitude targets, this paper proposes an evaluation index system for the combat effectiveness of the missile-antiaircraft weapon systems, and briefly analyzes the reasons for the selection of targets. Then, using expert scoring method, several training samples were obtained and the three-layer BP neural network constructed was trained. When the training accuracy reached the requirement, BP neural network was used to analyze several typical antiaircraft weapon systems The operational effectiveness of cruise missiles was evaluated. The results show that it is reasonable to use the trained BP neural network to evaluate the combat effectiveness of the missile-to-air defense weapon system based on the selected indicators, reducing the human factors in the assessment and making the evaluation results more credible. The results of the study can provide theoretical reference for the development and development of new type of AA combined with antiaircraft weapon system based on the existing weaponry and equipment.