A comparative study between LSTM and ARIMA for sales forecasting in retail
Food waste is a major environmental issue. Expired products are thrown away, implying that too much food is ordered compared to what is sold and that a more accurate prediction model is required within grocery stores. In this study the two prediction models Long Short-Term Memory (LSTM) and Autoregr...
| Main Authors: | , |
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| Format: | Others |
| Language: | English |
| Published: |
KTH, Skolan för elektroteknik och datavetenskap (EECS)
2018
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| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229747 |