Deep learning and smart energy-based lightweight urban power load forecasting model for sustainable urban growth
IntroductionUrban power load forecasting is essential for smart grid planning but is hindered by data imbalance issues. Traditional single-model approaches fail to address this effectively, while multi-model methods mitigate imbalance by splitting datasets but incur high costs and risk losing shared...
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Main Authors: | Haewon Byeon, Azzah AlGhamdi, Ismail Keshta, Mukesh Soni, Sultonali Mekhmonov, Gurpreet Singh |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-01-01
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Series: | Frontiers in Sustainable Cities |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/frsc.2024.1487109/full |
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