现代防御技术2025，Vol.53Issue(2)：175-182,8.DOI:10.3969/j.issn.1009-086x.2025.02.019
基于BP神经网络的备件满足率与利用率预测方法
Method for Predicting the Satisfaction and Utilization Rates of Spare Based on BP Neural Networks
王欣汝 1唐少康 1杨建军1
作者信息
- 1. 工业和信息化部电子第五研究所 装备综合保障研究中心,广东 广州 511370||广州赛宝腾睿信息科技有限公司,广东 广州 511370
- 折叠
摘要
Abstract
By leveraging the correspondence between spares configuration schemes and equipment support performance,the BP(back propagation)neural network model is used to adjust the mapping relationship between spares configuration schemes and their corresponding satisfaction and utilization rates.This facilitates the evaluation of the rationality of spares configuration scheme design.Using three types of equipment with different structural compositions as examples,the corresponding neural network prediction models for the satisfaction and utilization rates of spares are designed and trained with data samples.This achieves fast and high-precision calculations of the satisfaction and utilization rates of spare parts,with both the mean error and mean square error being less than 0.05%,demonstrating the effectiveness of the proposed method.关键词
备件配置方案/BP神经网络/保障效能/备件满足率/备件利用率Key words
spares configuration scheme/BP(back propagation)neural network/support efficiency/spares satisfaction rate/spares utilization rate引用本文复制引用
王欣汝,唐少康,杨建军..基于BP神经网络的备件满足率与利用率预测方法[J].现代防御技术,2025,53(2):175-182,8.
