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Demand forecasting with machine learning methods

Author(s): Jose Martin Rožanec (Author), Dunja Mladenić (Supervisor), Blaž Fortuna (Co-Supervisor)

Year: 2023

Type: Doctoral dissertation

This thesis examines how machine learning can be applied in demand forecasting. In particular, it describes a novel approach toward lumpy and intermittent demand forecasting. It advocates using a two-fold model for forecasting lumpy (irregular demand occurrence, strong demand size variability) and intermittent (irregular demand occurrence, little demand size variability) …