• Media type: E-Book
  • Title: Demand forecasting intermittent and lumpy time series: comparing statistical, machine learning and deep learning methods
  • Contributor: Kiefer, Daniel [Author]; Grimm, Florian [Author]; Bauer, Markus [Author]; van Dinther, Clemens [Author]
  • Published: Reutlingen: Hochschule Reutlingen, 2021
  • Extent: 1 Online-Ressource
  • Language: English
  • DOI: 10.24251/HICSS.2021.172
  • Identifier:
  • Origination:
  • Footnote: In: Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS-54), 4-8 January 2021, online. - Honolulu : University of Hawai'i at Manoa, 2021, S. 1425-1434. - ISBN 978-0-9981331-4-0
  • Access State: Open Access