Evaluation of Nonlinear Autoregressive Network with Exogenous Inputs Architectures for Wind Speed forecasting
This research investigates the optimal NARX neural network architecture for forecasting daily maximum wind speed in Dakhla, a region with substantial wind energy resources. Two configurations NARX-SP (open loop) and NARX-P (closed loop) were evaluated using the Levenberg-Marquardt algorithm, known f...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2025/11/epjconf_cofmer2025_05003.pdf |
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| Summary: | This research investigates the optimal NARX neural network architecture for forecasting daily maximum wind speed in Dakhla, a region with substantial wind energy resources. Two configurations NARX-SP (open loop) and NARX-P (closed loop) were evaluated using the Levenberg-Marquardt algorithm, known for its fast and efficient training. Predictive performance was assessed using RMSE to measure the gap between predicted and actual values. Results show that NARX-SP outperforms NARX-P, achieving lower RMSE and better forecasting accuracy. |
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| ISSN: | 2100-014X |