Evaluating statistical and machine learning models for river flow forecasting in Terengganu: a case study using facebook prophet, XGBoost, and random forest

Accurate forecasting of river flow is essential for effective flood management and sustainable water resource planning, particularly in regions influenced by seasonal monsoons like Terengganu, Malaysia. This study evaluates and compares the predictive performance of three forecasting models includin...

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Bibliographic Details

Main Authors:	Noraini, Ibrahim, Nur Amalina, Mat Jan, Norhaiza, Ahmad, Zanariah, Zainudin, Nurul Syafidah, Jamil, Basri, Badyalina, Ahmad Zaffry Hadi, Mohd Juffry
Format:	Conference or Workshop Item
Language:	en
Published:	IEEE 2025
Subjects:	QA Mathematics QA75 Electronic computers. Computer science
Online Access:	https://umpir.ump.edu.my/id/eprint/47305/1/Evaluating%20Statistical%20and%20Machine%20Learning%20Models%20for%20River%20Flow%20Forecasting%20in%20Terengganu%20A%20Case%20Study%20Using%20Facebook%20Prophet%20XGBoost%20and%20Random%20Forest.pdf https://umpir.ump.edu.my/id/eprint/47305/ https://doi.org/10.1109/AiDAS67696.2025.11212852
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