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Gone in 30 days! Predictions for car import planning

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Datum

2018

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De Gruyter

Zusammenfassung

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.

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Lacic, Emanuel; Traub, Matthias; Duricic, Tomislav; Haslauer, Eva; Lex, Elisabeth (2018): Gone in 30 days! Predictions for car import planning. it - Information Technology: Vol. 60, No. 4. DOI: 10.1515/itit-2017-0040. Berlin: De Gruyter. PISSN: 2196-7032. pp. 219-228

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