文章基本信息

标题：Forecasting method under the introduction of a day of the week index to the daily shipping data of sanitary materials
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作者：Komei Suzuki ; Hirotake Yamashita ; Kazuhiro Takeyasu 等
期刊名称：Journal of Computations & Modelling
印刷版ISSN：1792-7625
电子版ISSN：1792-8850
出版年度：2017
卷号：7
期号：2
出版社：Scienpress Ltd
摘要：
Correct sales forecasting is indispensable to industries. 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, we propose a new method to improve forecasting accuracy and confirm them by the numerical example. 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. First, we make estimation of ARMA model parameter and then estimate smoothing constants, which is the theoretical solution. Combining the trend removing method with this method, we aim to improve forecasting accuracy. Furthermore, “a day of the week index” is newly introduced for the daily data and the forecasting is executed to the manufacturer’s data of sanitary materials. We have obtained good result. The effectiveness of this method should be examined in various cases.
关键词：Minimum Variance; Exponential Smoothing Method; Forecasting; Trend; Sanitary Materials