Dynamic Prediction Method for Valuable Spare Parts Demand in Weaponry Equipment Based on Data Perception

Weiyi Wu, Yunxian Jia, Yangyang Zhang, B. Liu
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引用次数: 0

Abstract

Missile is an important weapon system of the army. The spare parts of missile equipment are significant effect on military operations. In order to improve the mission completion rate of missile equipment in wartime, thispaper introduces data sensing method to forecast the demand of valuablespare parts of missile equipment dynamically. Firstly, the information related to valuable spare parts of missile equipment was obtained by data sensing, and the sample size was determined by Bernoulli uniform sampling probability. Secondly, according to the data quality of multisource and multi-modal, the data requirement for dynamic demand prediction of valuable spare parts of missile equipment was obtained. Finally, according to the characteristics of the spare parts, the life of the spare parts was predicted, realizing the dynamic prediction of the demand for valuable spare parts of missile equipment. The results show that the demand of valuable spare parts of missile equipment can be predicted dynamically by using this method, the accuracy is higher than 95%, and the real-time performance is more excellent.
基于数据感知的武器装备有价备件需求动态预测方法
导弹是军队的重要武器系统。导弹装备的备件对军事行动具有重要影响。为了提高战时导弹装备的任务完成率,本文采用数据传感方法对导弹装备的易损件需求进行动态预测。首先,通过数据传感获得导弹装备有价值备件的相关信息,并通过伯努利均匀采样概率确定样本量。其次,根据多源多模态的数据质量,得到了导弹装备贵重零部件动态需求预测的数据需求。最后,根据备件的特点,对备件的寿命进行了预测,实现了对导弹装备贵重备件需求的动态预测。结果表明,该方法可以动态预测导弹装备贵重零部件的需求量,准确率高于95%,实时性更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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