| 李田科,沙卫晓,李伟,于仕财.一种战车主减速器温度预测方法研究[J].装备环境工程,2016,13(6):35-40. 李田科,沙卫晓,李伟,于仕财.Research on Temperature Prediction Method of Main Reducer for Chariot[J].Equipment Environmental Engineering,2016,13(6):35-40. |
| 一种战车主减速器温度预测方法研究 |
| Research on Temperature Prediction Method of Main Reducer for Chariot |
| 投稿时间：2016-03-16 修订日期：2016-11-24 |
| DOI：10.7643/ issn.1672-9242.2016.06.007 |
| 中文关键词: 误差修正因子 温度预测 ARIMA模型 BP神经网络 |
| 英文关键词:Error correction factors temperature prediction ARIMA model BP neural network |
| 基金项目:国家自然科学基金(61179017) |
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| 中文摘要: |
| 目的针对战车主减速器温度预测需求，方法建立时间序列ARIMA多步预测和BP神经网络预测模型，提出基于BP神经网络修正误差的ARIMA模型温度预测方法，结果结合BP神经网络的非线性能力与ARIMA模型预测能力，分析ARIMA在多步预测时误差产生原因，在神经网络对ARIMA多步误差进行预测基础上计算修正因子，把误差修正因子和BP网络结合，实现对多步预测误差的修正。结论通过预测值与实际值进行对比，可有效提高预测准确度。 |
| 英文摘要: |
| Objective Temperature prediction of main reducer is demanded.Methods It establish model of ARIMA multi-step prediction based on time series and BP neural network prediction.It put forward temperature prediction method of ARIMA model based on BP neural network correcting errors. Results The method combined nonlinear ability of BP neural network with prediction ability of ARIMA model.It analyze error caused when ARIMA multi-step prediction was used. Error correction factors is calculated based on neural network predicting ARIMA multi-step error. Multi-step prediction error is corrected by combing BP neural network with error correction factors. Conclusion Prediction accuracy is improved by comparison predictive value with actual value. |
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