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 |
|---|---|
| Pages (from-to) | 219-228 |
| Journal | Information Technology |
| Volume | 60 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Aug 2018 |
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