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Florian Grimm
Florian Grimm
Wissenschaftlicher Mitarbeiter, Hochschule Reutlingen
Verified email at reutlingen-university.de - Homepage
Title
Cited by
Cited by
Year
Demand forecasting intermittent and lumpy time series: Comparing statistical, machine learning and deep learning methods
D Kiefer, F Grimm, M Bauer, C Van Dinther
262021
Artificial Intelligence in Supply Chain Management: Investigation of Transfer Learning to Improve Demand Forecasting of Intermittent Time Series with Deep Learning
D Kiefer, F Grimm, D Van
Proceedings of the 55th Hawaii International Conference on System Sciences, 2022
32022
Sales forecasting under economic crisis: a case study of the impact of the COVID19 crisis to the predictability of sales of a medium-sized enterprise
M Bauer, D Kiefer, F Grimm
International Conference on Human-Centered Intelligent Systems, 163-172, 2021
12021
Univariate time series forecasting by investigating intermittence and demand individually
F Grimm, D Kiefer, M Bauer
International Conference on Human-Centered Intelligent Systems, 143-151, 2021
2021
Univariate time series forecasting: machine learning prediction of the best suitable forecast model based on time series characteristics
D Kiefer, M Bauer, F Grimm
International Conference on Human-Centered Intelligent Systems, 152-162, 2021
2021
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