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文章基本信息

  • 标题:Improving Forecasting Accuracy By Introducing a Day of the Week Index for the Daily Sanitary Materials’ Shipping Data
  • 本地全文:下载
  • 作者:Kazuhiro Takeyasu ; Hirotake Yamashita ; Daisuke Takeyasu
  • 期刊名称:Journal of Computations & Modelling
  • 印刷版ISSN:1792-7625
  • 电子版ISSN:1792-8850
  • 出版年度:2015
  • 卷号:5
  • 期号:3
  • 出版社:Scienpress Ltd
  • 摘要:

    In industries, how to improve forecasting accuracy such as sales, shipping is an important issue. There are many researches made on this. In this paper, a hybrid method is introduced and plural methods are compared. Focusing that the equation of exponential smoothing method(ESM) is equivalent to (1,1) order ARMA model equation, a new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Generally, smoothing constant is selected arbitrarily. But in this paper, we utilize above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate smoothing constants. Thus theoretical solution is derived in a simple way and it may be utilized in various fields. Combining the trend removing method with this method, we aim to improve forecasting accuracy. Furthermore, “a day of the week index” is newly introduced to the daily shipping data of sanitary materials and we have obtained good result. The effectiveness of this method should be examined in various cases.
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