銷售預測之自動化方法選擇：理論模型與實證研究

Demand Forecasting by Automatic Model Selection

古竺璉(Chu-Lien Ku)

指導教授 ： 孔令傑

國立臺灣大學/管理學院/企業管理碩士專班/碩士(2020年)

https://doi.org/10.6342/NTU202100054

摘要

NONE

關鍵字

需求預測 ； 自動化選擇 ； 時間序列 ； 移動平均 ； 線性迴歸 ； 指數平滑

並列摘要

In this thesis, we research a cosmetics company’s sales forecasting. We analyze the sales data from 2017 to 2020, a total of 38 months sales record. The objective of this study is to find the best forecasting model automatically. We implement twelve models using four time series forecasting methods, including Moving Average, Linear Regression, Exponential Smoothing, and Holt-Winter Exponential Smoothing, with three different ways of applying seasonality. Among the top 100 sales items, we improve the accuracy of forecasting averagely by 12.9% and increase the forecasting performance for more than half of the items by more than 20% by using the proposed models.

並列關鍵字

sales forecasting ； automatic model selection ； time series ； Moving Average ； Linear Regression ； Exponential Smoothing ； Holt-Winters Exponential Smoothing

參考文獻

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