期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2013
卷号：3
期号：1
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：We study the effect of decomposing time series into multiple components like trend, seasonal and irregular and performing the clustering on those components and generating the forecast values of each component separately. In this project we are working on sales data. Multiple forecast experts are used to forecast each component series. Statistical method ARIMA, Holt winter and exponential smoothing are used to forecast these components. We performed clustering for forecasting and discovered a set of best, good and bad forecasters. Selection of best, good and bad forecasters is performed on the basis of count and rank of expert id’s generated. Since we have thousands of experts, we experiment with combining method to get better forecast. Finally absolute percentage error (APE) is used for comparing forecast.
关键词：Time Series; Decomposition; Combining; Sales Forecasting; Clustering; APE
