Improving the accuracy of air relative humidity prediction using hybrid machine learning based on empirical mode decomposition: a comparative study
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11356-023-26779-8.pdf
Reference41 articles.
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2. Abdulhay E, Alafeef M, Alzghoul L, Al Momani M, Al Abdi R, Arunkumar N, ... & de Albuquerque VHC (2020). Computer-aided autism diagnosis via second-order difference plot area applied to EEG empirical mode decomposition. Neural Comput Appl 32(15):10947–10956. https://doi.org/10.1007/s00521-018-3738-0.
3. Adnan M, Adnan RM, Liu S, Saifullah M, Latif Y & Iqbal M (2021). Prediction of relative humidity in a high elevated basin of western Karakoram by using different machine learning models. Weather Forecast 59:. https://doi.org/10.5772/intechopen.98226.
4. Alaodolehei B, Jafarian K, Sheikhani A, Beni HM (2020) Performance enhancement of an achalasia automatic detection system using ensemble empirical mode decomposition denoising method. J Med Biol Eng 40(2):179–188. https://doi.org/10.1007/s40846-019-00497-4
5. Arulmozhi E, Basak JK, Sihalath T, Park J, Kim HT, Moon BE (2021) Machine learning-based microclimate model for indoor air temperature and relative humidity prediction in a swine building. Animals 11(1):222. https://doi.org/10.3390/ani11010222
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