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).
Authors
- Sarah Atifah Saruchi (ORCID: https://orcid.org/0000-0003-4516-890X)
- Ammar A. Al-Talib
- Seri Liyana Ezamzuri
Institutions
- Universiti Malaysia Pahang Al-Sultan Abdullah (MY)
- UCSI University (MY)
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
Funders
- Universiti Malaysia Pahang