火力与指挥控制2024,Vol.49Issue(11) :72-77.DOI:10.3969/j.issn.1002-0640.2024.11.010

基于ARIMA-BP组合模型在装备故障率预测的应用

Application of ARIMA-BP Combined Model in Equipment Failure Rate Prediction

于晓 魏成亮 马金龙
火力与指挥控制2024,Vol.49Issue(11) :72-77.DOI:10.3969/j.issn.1002-0640.2024.11.010

基于ARIMA-BP组合模型在装备故障率预测的应用

Application of ARIMA-BP Combined Model in Equipment Failure Rate Prediction

于晓 1魏成亮 1马金龙1
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作者信息

  • 1. 解放军32201部队,吉林 白城 137001
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摘要

装备故障率预测结果是否准确,直接影响装备维修性验证试验结果,为了提高装备故障率预测精度,提出了一种新的组合模型预测方式,利用时间序列ARIMA预测模型、BP神经网络模型分别对装备故障率进行预测,在两种单项模型预测基础上,利用误差平方和最小原则建立组合预测模型,对装备故障率进行预测.预测结果表明,组合预测模型能够很好地提取装备故障率数据的线性特征和非线性特征,预测结果精度要高于两个单项模型.

Abstract

Whether the prediction result of equipment failure rate is accurate or not directly affects the result of equipment maintainability verification test.In order to improve the prediction accuracy of equip-ment failure rate,a new combined model prediction mode is proposed.The time series ARIMA prediction model and BP neural network model are used to predict the equipment failure rate respectively,and then on the basis of the two kinds of single item of model prediction,the error squares and the minimum principle are used to establish the combined prediction model to predict the equipment failure rate.The prediction results show that the combined prediction model can extract the linear and nonlinear characteristics of equipment fail-ure rate data well,and the accuracy of prediction result is higher than that of the two single models.

关键词

ARIMA模型/BP神经网络模型/组合预测模型/装备故障率

Key words

ARIMA model/BP neural network model/combined prediction model/equipment failure rate

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出版年

2024
火力与指挥控制
火力与指挥控制研究会,火力与指挥控制专业情报网

火力与指挥控制

CSTPCDCSCD北大核心
影响因子:0.312
ISSN:1002-0640
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