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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-96872-w |