Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Forecasting Industry Big Data with Holt Winter’s Method from a Perspective of In-Memory Paradigm
verfasst von : Sudipto Shankar Dasgupta, Prabal Mahanta, Rupam Roy, Ganapathy Subramanian
Erschienen in: On the Move to Meaningful Internet Systems: OTM 2014 Workshops
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Industrial data in time series exhibit seasonal behavior like demand for materials for any Industry and this call for seasonal forecasting which is of considerable importance for any planning for an industry as the business profitability revolves around the decisions based on the results of forecasting. This paper tries to explore the situations in the business industry domain which concentrates on the analysis of seasonal time series data using Holt-Winters exponential smoothing methods and along with this exploration the paper tries to optimize most of the intermediate stage for detailed analysis using in-memory database and sql techniques.