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

Abstract 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 artific...

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Autores principales: Marwah Sattar Hanoon, Ali Najah Ahmed, Nur’atiah Zaini, Arif Razzaq, Pavitra Kumar, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/960c7fe548c048e181298b3277450f28
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