基于ARMA模型的备件需求预测

X. Ren, Xiao-Fei Zhang
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引用次数: 0

摘要

从时间序列的因素入手,分析时间的高低、数据的类型、预测的准确性等,根据数据序列的特点进行分析。ARMA模型预测的序列要求必须是稳定的,即各因素在研究对象的时间范围内必须受到相同的要求。如果给定序列不是平稳序列,则必须对给定序列做预处理,使其平滑,然后通过ARMA模型。利用Eview软件进行实例分析,验证了模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spare parts demand forecasting based on ARMA model
Starting from the time series of factors, the level of analysis time, data types, and forecasting accuracy, based on the characteristics of the data sequence to be analyzed. ARMA model to predict sequence requirements must be stable, that factors in the time range of the study subjects must be subjected to the same requirements. If the given sequence is not stationary sequence, you must do on a given sequence of preprocess, smoothing it, then by ARMA model. Example is analyzed by Eview software, the validity of the model is verified.
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