Developing machine learning algorithms for meteorological temperature and humidity forecasting at Terengganu state in Malaysia

Accurately predicting meteorological parameters such as air temperature and humidity plays a crucial role in air quality management. This study proposes different machine learning algorithms: Gradient Boosting Tree (G.B.T.), Random forest (R.F.), Linear regression (LR) and different artificial neura...

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Detalles Bibliográficos
Autores principales: Hanoon, Marwah Sattar, Ahmed, Ali Najah, Zaini, Nur’atiah, Razzaq, Arif, Kumar, Pavitra, Sherif, Mohsen, Sefelnasr, Ahmed, El-Shafie, Ahmed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8460791/
https://www.ncbi.nlm.nih.gov/pubmed/34556676
http://dx.doi.org/10.1038/s41598-021-96872-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8460791/
https://www.ncbi.nlm.nih.gov/pubmed/34556676
http://dx.doi.org/10.1038/s41598-021-96872-w

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