Webseite TUM Campus Straubing, Professorship Bioinformatics
Predicting the future based on historical observations is a common problem in many areas. For this purpose, modern statistical and machine learning based methods for Time Series Forecasting are widely applied. Some of the best performing modern approaches were developed based on large datasets, which are usually not available in small and medium-sized companies. The goal of this thesis is to evaluate whether they are nevertheless applicable for horticultural sales predictions based on datasets provided by partner companies.
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