TF-CEP: carbon emission prediction with data augmentation and temporal-frequency fusion contrasting
Abstract In the context of low-carbon power development, accurate prediction of the carbon emission intensity of the power system can provide data support for the optimization strategy of carbon emission reduction, thus helping to reduce the carbon emissions of the power system. At present, carbon e...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Series: | Discover Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44163-025-00408-4 |
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