ACS Applied Computer Science

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INTERMITTENT DEMAND FORECASTING USING DATA MINING TECHNIQUES

Intermittent demand occurs randomly with changing values and a lot of periods having zero demand. Ad hoc intermittent demand forecasting techniques have been developed which take special intermittent demand characteristics into account. Besides traditional techniques and specialized methods, data mining offers a better alternative for intermittent demand forecasting since data mining methods are powerful techniques. This study contributes to the current literature by showing the benefit of using data mining methods for intermittent demand forecasting purpose by comprising mostly used data mining methods.

  • APA 6th style
Kaya, G. O., & Turkyilmaz, A. (2018). Intermittent demand forecasting using data mining techniques. Applied Computer Science, 14(2), 38-47. doi:10.23743/acs-2018-11
  • Chicago style
Kaya, Gamze Ogcu, and Ali Turkyilmaz. "Intermittent Demand Forecasting Using Data Mining Techniques." Applied Computer Science 14, no. 2 (2018): 38-47.
  • IEEE style
G. O. Kaya and A. Turkyilmaz, "Intermittent demand forecasting using data mining techniques," Applied Computer Science, vol. 14, no. 2, pp. 38-47, 2018.
  • Vancouver style
Kaya GO, Turkyilmaz A. Intermittent demand forecasting using data mining techniques. Applied Computer Science. 2018;14(2):38-47.