Search Results (2)
Demand forecasting with machine learning methods
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) …
Semi-automatic ontology construction
This thesis addresses the task of formalizing and implementing the process of semi-automatic ontology construction. We propose a theoretical framework for formalizing the ontology construction process. The process is described as a sequence of operators applied to the ontology. Several types of common operators are identified and each type is …