Abstract
A challenge for importers in the automobile industry is adjusting to rapidly changing market demands. In this work, we describe a practical study of car import planning based on the monthly car registrations in Austria. We model the task as a data driven forecasting problem and we implement four different prediction approaches. One utilizes a seasonal ARIMA model, while the other is based on LSTM-RNN and both compared to a linear and seasonal baselines. In our experiments, we evaluate the 33 different brands by predicting the number of registrations for the next month and for the year to come.
Original language | English |
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Pages (from-to) | 219-228 |
Journal | Information Technology |
Volume | 60 |
Issue number | 4 |
DOIs | |
Publication status | Published - Aug 2018 |