Short-term temperature forecasts using a convolutional neural network — An application to different weather stations in Germany
Local temperature forecasts for horizons up to 24 h are required in many applications. A common method to generate such forecasts is the Seasonal Autoregressive Integrated Moving Average (SARIMA) model or, much simpler, the naïve forecast. In this paper, we test whether deep neural networks are able...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-12-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827020300074 |