摘要
针对传统的备件需求预测方法主观性强,缺乏科学性等问题,以通信部队野外驻训为背景,从备件需求影响因素出发,提出一种基于BP神经网络的预测算法。对备件精确保障及需求预测和BP神经网络及其适用范围进行简要介绍,分析了备件需求影响因素,以某型电台的功放模型为样板,对BP神经网络预测算法的适用性进行了检测。结果表明,该方法能很好地提高备件需求预测精度,满足装备保障精确化的要求。
Solving the traditional estimation of spare part requirement is very subjectivity and is not scientifically, put forward an estimation method based on BP neural network （NN） on the background of field drill of communication army by analyzing the influence factors of field drill. It also introduces spare part precise supporting and requirement estimation and BP NN and their acclimatization, analyses the influence factors of field drill, tests the applicability of the BP algorithm on the former of one transmitter-receiver＇s power amplifier. The result shows that the algorithm can greatly improve precision of spare part estimation, also it can meet the need of accurate maintenance support in future warfare.
出处
《兵工自动化》
2010年第3期33-34,37,共3页
Ordnance Industry Automation
关键词
人工神经网络
需求预测
误差反向传播算法
精确保障
ANN
Requirement estimation
Error oppositely-directed algorithm
Precision support
