Comparison of machine learning model performance for predicting the climate variables in Johor Bahru, Malaysia

Comparison of machine learning model performance for predicting the climate variables in Johor Bahru, Malaysia

Abstract Accurately predicting climate variables such as air temperature, humidity and precipitation plays a crucial role in air quality management. This research aims to provide preliminary information that can shed lights to local stakeholders for climate adaptation strategies in Johor Bahru city,...

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Bibliographic Details
Main Authors: Farid Zamani Che Rose, Nur Aqilah Khadijah Rosili, Muhammad Fadhil Marsani
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Machine learning
Prediction
Temperature
Humidity
Precipitation
Adaptation
Online Access:https://doi.org/10.1038/s41598-025-08033-y
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