INTERMITTENT DEMAND FORECASTING USING DATA MINING TECHNIQUES

Autor:	Gamze Ogcu KAYA, Ali TURKYILMAZ
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	ANN support vector regressions Intermittent Demand Forecasting Information technology T58.5-58.64 Electronic computers. Computer science QA75.5-76.95
Zdroj:	Applied Computer Science, Vol 14, Iss 2, Pp 38-47 (2018)
Druh dokumentu:	article
ISSN:	1895-3735 2353-6977
DOI:	10.23743/acs-2018-11
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/efb9a8d43dbc4217aba99eacb1f3b1a4 Zobrazit plný text záznamu View record in DOAJ