mimakhdumi/Fire-Weather-Index-Predictor

A Flask-based Machine Learning web application that predicts the Fire Weather Index (FWI) using meteorological data from the Algerian Forest Fires dataset. # Algerian Forest Fire (FWI) Prediction This is a machine learning web application designed to predict the **Fire Weather Index (FWI)** based on the **Algerian Forest Fires dataset**. The application allows users to input meteorological data via a user-friendly web interface and receive an instant prediction of fire intensity. ## 🚀 Project Overview Forest fires are a severe environmental issue. This project aims to assist in fire risk assessment by predicting the FWI, which estimates the danger of wildfire based on weather conditions. The model was trained on data collected from the Bejaia and Sidi Bel-abbes regions of Algeria. ## 🛠️ Tech Stack * **Frontend:** HTML5, CSS3, Jinja2 (Responsive Design) * **Backend:** Python, Flask * **Machine Learning:** Scikit-learn, Pandas, NumPy * **Dataset:** Algerian Forest Fires Dataset (UCI) ## 📊 Features The application accepts the following input parameters to generate a prediction: * **Temperature:** (°C) * **RH:** Relative Humidity (%) * **Ws:** Wind Speed (km/h) * **Rain:** (mm) * **FFMC:** Fine Fuel Moisture Code * **DMC:** Duff Moisture Code * **ISI:** Initial Spread Index * **Classes:** Fire (1) or Not Fire (0) * **Region:** Bejaia (0) or Sidi Bel-abbes (1) ## 🔧 Installation & Run 1. Clone the repository: ```bash git clone github.com ``` 2. Install dependencies: ```bash pip install -r Requirements.txt ``` 3. Run the Flask app: ```bash python app.py ``` 4. Open your browser and navigate to `localhost`.