ML-basierte Absatzprognose mit Frühindikatoren

Research output: Journal contributionsJournal articlesResearchpeer-review


Operating in an environment characterised by uncertainty poses challenges for companies. machine learning (ML) methods, with the inclusion of external factors, offer the possibility of producing long-term demand forecasts more precisely than conventional statistical forecasting methods. In this paper, the potential of ML with the inclusion of leading indicators (e. g. economic data) for the demand forecasts of one product of a chemical company is shown.
Translated title of the contributionML-based Demand Forecast with External Factors
Original languageGerman
JournalZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb
Issue number5
Pages (from-to)324-329
Number of pages6
Publication statusPublished - 16.05.2023

Bibliographical note

Publisher Copyright:
© 2023 Walter de Gruyter GmbH, Berlin/Boston, Germany.

    Research areas

  • Engineering - Demand Forecasting, time series analysis, artificial intelligence, Machine Learning, External factors