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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Bibliographic Details
Main Authors: Mohammed Diykh, Mumtaz Ali, Abdulhaleem H. Labban, Ramendra Prasad, Mehdi Jamei, Shahab Abdulla, Aitazaz Ahsan Farooque
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Results in Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025006759
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