Comparative Analysis of Machine Learning Algorithms for Rainfall Prediction in Kuantan, Pahang, Malaysia.

This study compares the performance and accuracy of four ML algorithms which are Support Vector Regressor (SVR), Artificial Neural Network (ANN), Random Forest Regressor (RFR), and Linear Regression (LR) in the rainfall prediction application.All four methods employ the same input parameters which are temperature (c), dew point (c), humidity (%), wind speed (Kph) and pressure (Hg).Meanwhile the output parameter is set to be the rainfall (mm) which indicates the precipitation in Kuantan, Pahang, Malaysia.The analysis shows that the SVR consistently outperforms the other machine learning algorithms, achieving the lowest Mean Absolute Error (MAE) and Mean Squared Error (MSE).

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Publication Details

Journal
Proceedings of International Conference on Artificial Life and Robotics
Published
2025-02-13
DOI
https://doi.org/10.5954/icarob.2025.os13-4
Primary Topic
Hydrological Forecasting Using AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Comparative Analysis of Machine Learning Algorithms for Rainfall Prediction in Kuantan, Pahang, Malaysia.

Sarah Atifah Saruchi, Ammar A. Al-Talib, Seri Liyana Ezamzuri
Proceedings of International Conference on Artificial Life and Robotics
Hydrological Forecasting Using AI
article

Comparative Analysis of Machine Learning Algorithms for Rainfall Prediction in Kuantan, Pahang, Malaysia.

Sarah Atifah Saruchi, Ammar A. Al-Talib, Seri Liyana Ezamzuri
article en

Abstract

This study compares the performance and accuracy of four ML algorithms which are Support Vector Regressor (SVR), Artificial Neural Network (ANN), Random Forest Regressor (RFR), and Linear Regression (LR) in the rainfall prediction application.All four methods employ the same input parameters which are temperature (c), dew point (c), humidity (%), wind speed (Kph) and pressure (Hg).Meanwhile the output parameter is set to be the rainfall (mm) which indicates the precipitation in Kuantan, Pahang, Malaysia.The analysis shows that the SVR consistently outperforms the other machine learning algorithms, achieving the lowest Mean Absolute Error (MAE) and Mean Squared Error (MSE).

Proceedings of International Conference on Artificial Life and RoboticsVol. 30
Universiti Malaysia Pahang Al-Sultan Abdullah (MY), UCSI University (MY)
Universiti Malaysia Pahang
Climate action
Openalex Percentile: Top 87%
Hydrological Forecasting Using AI
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Comparative Analysis of Machine Learning Algorithms for Rainfall Prediction in Kuantan, Pahang, Malaysia. — Sarah Atifah Saruchi, Ammar A. Al-Talib, et al. · Proceedings of International Conference on Artificial Life and Robotics (2025) | TGRS Research Map | TGRS