EMD-Att-LSTM: A Data-driven Strategy Combined with Deep Learning for Short-term Load Forecasting
Electric load forecasting is an efficient tool for system planning, and consequently, building sustainable power systems. However, achieving desirable performance is difficult owing to the irregular, nonstationary, nonlinear, and noisy nature of the observed data. Therefore, a new attention-based en...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | Journal of Modern Power Systems and Clean Energy |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9540798/ |