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当前局势多变且节奏迅速的现代高新技术战争使得航空装备需求量与损耗率激增,航空装备保障人员也面临着战时保障情况复杂、决策难度增加的问题.在BP神经网络的基础上使用灰色理论对其进行了优化,将得到的灰色BP神经网络对航空装备作战携行数量进行了预测并与一般BP神经网络和GM(1,1)模型预测结果对比.结果表明:灰色BP神经网络预测精度高、收敛速度快、所需样本数据少,对航空装备作战携行数量预测具有重要价值.
The modern high-tech warfare, which is changing rapidly at a fast pace, has caused a surge in demand and loss rate of aviation equipment. Aviation equipment support personnel also face the problem of complex warfighting support and increased difficulty in decision making. Based on the BP neural network, The results show that the prediction accuracy of gray BP neural network is better than that of general BP neural network and GM (1,1) model. High speed of convergence, less required sample data and great value in forecasting the number of aircraft equipment carriers.