pranshul30/Major_project

This project predicts the Fire Weather Index (FWI) for two regions in Algeria: Sidi-Bel and Brjaia. The FWI is a crucial indicator used to estimate the likelihood of forest fires based on environmental parameters. The model has been developed using Machine Learning (ML) algorithms to assist in early fire detection and risk management. # Algerian Forest Fire Prediction This project predicts the **Fire Weather Index (FWI)** for two regions in Algeria: **Sidi-Bel** and **Brjaia**. The FWI is a crucial indicator used to estimate the likelihood of forest fires based on environmental parameters. The model has been developed using **Machine Learning (ML)** algorithms to assist in early fire detection and risk management. ## Table of Contents - Overview - Features - Dataset - Model - Tech Stack - Usage - Screenshots - Future Enhancements - Contributing ## Overview The project provides a web-based interface where users can input various environmental factors such as temperature, humidity, wind speed, and rainfall to predict the Fire Weather Index. Based on the FWI value, the risk level of a forest fire is categorized from **Low** to **Extreme**. ## Features - Predicts Fire Weather Index (FWI) using ML. - Supports prediction for two regions: **Sidi-Bel** and **Brjaia**. - Provides visual indicators for fire risk levels. - User-friendly web interface for input and result display. ## Dataset Kaggle-kaggle.com The dataset used in this project contains historical environmental data including: - Temperature (°C) - Relative Humidity (%) - Wind Speed (km/h) - Rainfall (mm) - Fine Fuel Moisture Code (FFMC) - Duff Moisture Code (DMC) - Initial Spread Index (ISI) - Region Classification (0: Brjaia, 1: Sidi-Bel) Source: Kaggle Notebook Description: The dataset contains 244 records of environmental data collected from: Bejaia (Northeast Algeria) – 122 instances Sidi Bel-Abbes (Northwest Algeria) – 122 instances Period: June to September, 2012 Features: Date: (DD/MM/YYYY) Temperature (°C): 22 to 42 Relative Humidity (%): 21 to 90 Wind Speed (km/h): 6 to 29 Rainfall (mm): 0 to 16.8 FWI System Components: FFMC (28.6 to 92.5) DMC (1.1 to 65.9) DC (7 to 220.4) ISI (0 to 18.5) BUI (1.1 to 68) FWI (0 to 31.1) Target …