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Forecasting accuracy analysis based on two new heuristic methods and Holt-Winters-Method

机译:基于两种新的启发式方法和Holt-Winters方法的预测精度分析

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Since 1970s, many academic researchers and business practitioners have started to develop different forecasting methods and models. Most of them are still used in the IT-Systems nowadays. However, they don't perform well enough in practice. People pay much attention to data collection but ignore the data quality, which could lead to low forecasting accuracy. In this paper, we will introduce two new heuristic business forecasting techniques (Revinda and Metrix). Both methods utilize inherent structures of time series. The error analysis is based on B2C and B2B aggregated commercial data. In addition, these two methods will be compared with HoLT-WiNTERS-Methods (HWM) by using error measures MAPE, percentage better and Theil's U2.
机译:自1970年代以来,许多学术研究人员和商业从业人员开始开发不同的预测方法和模型。如今,大多数仍在IT系统中使用。但是,它们在实践中表现不够好。人们非常重视数据收集,却忽略了数据质量,这可能会导致预测准确性降低。在本文中,我们将介绍两种新的启发式业务预测技术(Revinda和Metrix)。两种方法都利用时间序列的固有结构。误差分析基于B2C和B2B汇总的商业数据。另外,将通过使用误差度量MAPE,更好的百分比和Theil的U2将这两种方法与HoLT-WiNTERS-方法(HWM)进行比较。

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