An obvious seasonality appears in customer demand of many industries. It can have a repetition period from a month to a year. In this paper, researchers use a hybrid learning method to improve sales forecast and supply chain management. This hybrid method combines Stable Seasonal Pattern (SSP) and Support Vector Regression (SVR) analysis. It provides a flexible approach which gives accurate forecast for budget and manufacture planning of companies. © 2013 Springer Science+Business Media New York.
CITATION STYLE
Ye, F., & Eskenazi, J. (2013). Sales forecast using a hybrid learning method based on stable seasonal pattern and support vector regression. In Lecture Notes in Electrical Engineering (Vol. 236 LNEE, pp. 1251–1259). Springer Verlag. https://doi.org/10.1007/978-1-4614-7010-6_139
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