Designing empirical fourier decomposition reinforced with multiscale increment entropy and deep learning to forecast dry bulb air temperature
Accurate prediction of dry bulb air temperature (DBTair) is significant to determine the state of humid air and supporting experts in the environmental sector. Traditional machine learning based approaches struggle to deliver accurate predictions when temperature is suddenly fluctuated during extrem...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025006759 |
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