Short-Term Load Forecasting Based on Pelican Optimization Algorithm and Dropout Long Short-Term Memories–Fully Convolutional Neural Network Optimization
In order to improve the prediction accuracy of short-term power loads in a power system, this paper proposes a short-term load prediction method (POA-DLSTMs-FCN) based on a combination of multi-layer lost long short-term memory (DLSTM) neural networks, fully convolutional neural networks (FCNs) and...
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| Main Authors: | Haonan Wang, Shan Huang, Yue Yin, Tingyun Gu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/17/23/6115 |
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