Transfer Learning for Sales Volume Forecasting Using Convolutional Neural Networks
Improved time series forecasting accuracy can enhance demand planning, and therefore save money and reduce environmental impact. The idea behind this degree project is to explore transfer learning for time series forecasting. This has boiled down to two concrete goals. The first one is to examine if...
Main Author: | Alsterman, Marcus |
---|---|
Format: | Others |
Language: | English |
Published: |
KTH, Skolan för elektroteknik och datavetenskap (EECS)
2019
|
Subjects: | |
Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-255007 |
Similar Items
-
Hierarchical sales forecasting using Recurrent Neural Networks
by: Besharat Pour, Shiva
Published: (2020) -
Temporal Convolutional Networks for Forecasting Patient Volumes in Digital Healthcare
by: Berglind, Jonathan
Published: (2019) -
Forecasting Financial Time Series through Causal and Dilated Convolutional Neural Networks
by: Börjesson, Lukas
Published: (2020) -
Hyperparameter Optimization for Convolutional Neural Networks
by: Gousseau, Clément
Published: (2020) -
Pedestrian trajectory prediction with Convolutional Neural Networks
by: Zamboni, Simone
Published: (2020)