Published June 3, 2026
| Version v1
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Machine Learning-Based Hourly Solar Irradiance Forecasting for Jimma City, Ethiopia: A Seasonal Performance Analysis
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Description
Python scripts (preprocessing.py and modeling.py) for the paper titled 'Machine Learning-Based Hourly Solar Irradiance Forecasting for Jimma City, Ethiopia: A Seasonal Performance Analysis'. The scripts load NASA POWER hourly GHI data, perform feature engineering, train four machine learning models (Linear Regression, Random Forest, SVR, XGBoost), and generate all evaluation figures.
Files
Files
(18.9 kB)
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md5:15bae66a582b6b1e1086a52a217da73f
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13.1 kB | Download |
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md5:3d9269db71cb0d8011d641f192befc1d
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5.8 kB | Download |