Gone in 30 days! Predictions for car import planning

Autor:	Matthias Traub, Emanuel Lacic, Elisabeth Lex, Eva Haslauer, Tomislav Duricic
Rok vydání:	2018
Předmět:	Transport engineering General Computer Science Computer science business.industry 020209 energy 0202 electrical engineering electronic engineering information engineering Information technology 02 engineering and technology business
Zdroj:	it - Information Technology. 60:219-228
ISSN:	2196-7032 1611-2776
DOI:	10.1515/itit-2017-0040
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::53de8ea0372dd9a78ca5b0b9abef428d https://doi.org/10.1515/itit-2017-0040 Zobrazit plný text záznamu