yuvraj-singh047/Algerian-Forest-Fire

# 🔥 Algerian Forest Fire Weather Index Predictor A Machine Learning-based web application that predicts the **Fire Weather Index (FWI)** using environmental and forest condition inputs. Built using **Flask**, **Scikit-learn**, and **HTML/CSS**. --- ## 🚀 Project Overview Forest fires are highly dependent on weather and forest conditions. This project uses a trained ML regression model to predict the **Fire Weather Index**, helping assess fire risk levels based on user inputs. The application provides: - A clean web interface - Real-time predictions - Proper scaling and ML pipeline integration --- ## 🧠 Machine Learning Pipeline 1. User enters environmental parameters 2. Data is preprocessed using a trained **StandardScaler** 3. Prediction is generated using a trained ML model 4. Result is displayed on the web interface --- ## 📥 Input Features | Feature | Description | |---------|-------------| | **Temperature** | Temperature in °C | | **RH** | Relative Humidity (%) | | **Ws** | Wind Speed (km/h) | | **Rain** | Rainfall (mm) | | **FFMC** | Fine Fuel Moisture Code | | **DMC** | Duff Moisture Code | | **DC** | Drought Code | | **ISI** | Initial Spread Index | | **BUI** | Buildup Index | --- ## 📤 Output - **Predicted Fire Weather Index (FWI)** - Rounded and displayed cleanly on the UI --- ## 🛠️ Tech Stack - **Backend:** Flask (Python) - **Machine Learning:** Scikit-learn, NumPy - **Frontend:** HTML, CSS - **Model Serialization:** Pickle --- ## 📁 Project Structure ``` Algerian-Forest-Fire/ │ ├── Backend/ │ └── app.py │ ├── data/ │ └── Algerian_forest_fires_cleaned_data.csv │ ├── Frontend/ │ ├── static/ │ │ └── style.css │ └── templates/ │ └── index.html │ ├── models/ │ ├── model.pkl │ └── scaler.pkl │ ├── notebooks/ │ └── Algerian_forest_fires_model.ipynb │ ├── requirements.txt └── README.md ``` --- ## ⚙️ How to Run Locally ### 1️⃣ Clone the repository ```bash git clone github.com. …