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Machine Learning-Based Hourly Solar Irradiance Forecasting for Jimma City, Ethiopia: A Seasonal Performance Analysis

Domain:

environment and energy

Record type:

softwarepaper
Creator:
Sem
Publisher:
Zenodo
Host:avatar

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.

Visit

doi.org

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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