DevEliteHQ/algerian_forest_fire

# Algerian Forest Fire Prediction A machine learning-based application for predicting forest fires in Algeria using historical data and environmental factors. ## Features - Machine Learning model for forest fire prediction - Interactive web interface for predictions - Data visualization and analysis - RESTful API for model inference ## Algerian Forest Fires Dataset The dataset includes 244 instances that regroup a data of two regions of Algeria, namely the Bejaia region located in the northeast of Algeria and the Sidi Bel-abbes region located in the northwest of Algeria. - 122 instances for each region - Period: June 2012 to September 2012 - 11 attributes and 1 output attribute (class) - 244 instances classified into: fire (138 classes) and not fire (106 classes) ### Attribute Information: 1. **Date**: (DD/MM/YYYY) Day, month ('june' to 'september'), year (2012) **Weather Data Observations:** 2. **Temp**: Temperature noon (temperature max) in Celsius degrees: 22 to 42 3. **RH**: Relative Humidity in %: 21 to 90 4. **Ws**: Wind speed in km/h: 6 to 29 5. **Rain**: Total day in mm: 0 to 16.8 **FWI Components:** 6. **FFMC**: Fine Fuel Moisture Code index from the FWI system: 28.6 to 92.5 7. **DMC**: Duff Moisture Code index from the FWI system: 1.1 to 65.9 8. **DC**: Drought Code index from the FWI system: 7 to 220.4 9. **ISI**: Initial Spread Index index from the FWI system: 0 to 18.5 10. **BUI**: Buildup Index index from the FWI system: 1.1 to 68 11. **FWI**: Fire Weather Index: 0 to 31.1 12. **Classes**: two classes, namely Fire and not Fire ## Tech Stack ### Backend - Python - FastAPI - Poetry for dependency management - Machine Learning libraries (scikit-learn, pandas, etc.) ### Frontend - React.js - Node.js - Modern UI components ## Getting Started ### Prerequisites - Python 3.8+ - Node.js 14+ - Poetry (Python package manager) - npm (Node.js package manager) ## Acknowledgments - Algerian Forest Fires Dataset contributors - Scientific research pape …