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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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Published: |
Nature Portfolio
2021
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/33889/ |
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