Machine Learning + Streamlit | Predict Fuel Blend Properties with Ease
The Fuel Blend Properties Prediction System is a Machine Learning-powered solution that predicts 10 essential fuel blend properties based on:
- Component Fractions
- Component Properties
This project helps refineries, engineers, and researchers optimize fuel blends for better efficiency, performance, and sustainability.
✅ Predict 10 different blend properties
✅ Streamlit Web Interface for real-time predictions
✅ Multi-Output Regression using Linear Regression
✅ Export predictions as CSV
✅ Saves trained model as Pickle (.pkl)
| Component | Technology |
|---|---|
| Language | Python (3.8+) |
| Libraries | Pandas, Scikit-learn |
| UI | Streamlit |
| Model | MultiOutput Linear Regression |
Fuel-Blend-Properties-Prediction-System/ │── train.csv # Training dataset │── test.csv # Test dataset │── model.py # ML model training script │── app.py # Streamlit interface │── fuel_blend_model.pkl # Saved ML model │── predictions.csv # Output predictions │── requirements.txt # Dependencies │── README.md # Project documentation
