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This repository contains the full machine learning workflow to predict Global Horizontal Irradiance (GHI) using Saudi Arabia’s weather data (2015–2020).

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☀️ Solar Radiation ML Models – Saudi Arabian Dataset

This repository contains the full machine learning workflow to predict Global Horizontal Irradiance (GHI) using Saudi Arabia’s weather data (2015–2020).

🔍 Objectives

  • Train & compare multiple ML models (Linear Regression, RF, XGB, etc.)
  • Evaluate with MAE, RMSE, R²
  • Export best model for deployment

🧪 Models Evaluated

  • Linear Regression ✅
  • Random Forest
  • XGBoost
  • Histogram Gradient Boosting
  • Support Vector Regression
  • Artificial Neural Networks
  • Decision Tree
  • KNN

📁 Contents

  • notebooks/: Model training and evaluation
  • models/: Saved .pkl files
  • dataset/: Cleaned sample dataset
  • requirements.txt: Library dependencies

📌 Highlights

  • Best R²: 0.97 (Linear Regression)
  • 21 input features including DHI, DNI, humidity, wind speed
  • 10-fold and 43-fold cross-validation

🔗 Live App (Deployed Model)

See deployment repo here: (https://solar-radiation-prediction-using-saudi.onrender.com)

🔗 Related Repositories:

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This repository contains the full machine learning workflow to predict Global Horizontal Irradiance (GHI) using Saudi Arabia’s weather data (2015–2020).

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