Rainfall Prediction Using Integrated Machine Learning Models With K-Means Clustering: A Representative Case Study of Harirud Murghab Basin-Afghanistan

Rainfall Prediction Using Integrated Machine Learning Models With K-Means Clustering: A Representative Case Study of Harirud Murghab Basin-Afghanistan

Accurate rainfall prediction was essential for effective water resource management and disaster preparedness, especially in regions with limited observational data such as Afghanistan. This study objective was to develop a reliable rainfall prediction machine learning (ML) model by integrating satel...

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Bibliographic Details
Main Authors: Ziaul Haq Haq Doost, Ali Alsuwaiyan, Abdulazeez Abdulraheem, Nabil M. Al-Areeq, Zaher Mundher Yaseen
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Climate change
machine learning
rainfall prediction
time series analysis
Online Access:https://ieeexplore.ieee.org/document/11045676/
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https://ieeexplore.ieee.org/document/11045676/

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