Recurrent Neural Networks for Short-Term Load Forecasting An Overview and Comparative Analysis /
The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective forecasting system. Significant research has thu...
| Κύριοι συγγραφείς: | , , , , |
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| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
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| Σειρά: | SpringerBriefs in Computer Science,
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Introduction
- Properties and Training in Recurrent Neural Networks
- Recurrent Neural Networks Architectures
- Other Recurrent Neural Networks Models
- Synthetic Time Series
- Real-World Load Time Series
- Experiments
- Conclusions. .
