Deep residual networks with convolutional feature extraction for Short-Term Load Forecasting (STLF)
Conventional deep learning models struggle with balancing feature extraction and long-term temporal representation in Short-Term Load Forecasting (STLF). This study proposes a Convolutional Neural Network–Embedded Deep Residual Network (CNN-Embedded DRN) designed to enhance early-stage feature extra...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Nature Research
2026
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/123376/1/123376.pdf http://psasir.upm.edu.my/id/eprint/123376/ https://www.nature.com/articles/s41598-026-35410-y?error=cookies_not_supported&code=219662d0-780d-424a-ba26-754237083542 |
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