Navanethank/Algerian-Forest-Fire-Prediction

# 🔥 Algerian Forest Fire Prediction --- ## 🌲 Project Overview **Algerian Forest Fire Prediction** is a Machine Learning based web application designed to predict the possibility of forest fires using environmental and meteorological conditions. The project uses historical forest fire data from Algeria to train a Machine Learning model and provides an interactive web interface where users can enter environmental parameters and obtain a prediction. The application combines: - 🌡️ Environmental data - 💨 Weather conditions - 🌲 Forest-related factors - 🤖 Machine Learning - 🌐 Flask web application - 📊 Data analysis to build an intelligent forest fire prediction system. --- ## 🎯 Problem Statement Forest fires are a serious environmental problem that can cause: - 🌳 Loss of forests - 🐾 Wildlife destruction - 🌫️ Air pollution - 🏘️ Property damage - 👨‍🚒 Risk to human life - 🌍 Environmental imbalance Early prediction of fire risk can help authorities and environmental organizations take preventive action. ### Objective The main objective of this project is to develop a Machine Learning system capable of predicting whether forest fire conditions are likely to occur based on environmental and weather parameters. --- # 🚀 Key Features ### 🔥 Forest Fire Prediction Predict whether the given environmental conditions indicate a potential forest fire. ### 🌡️ Weather-Based Prediction The model uses important meteorological parameters to determine fire risk. ### 📊 Data Analysis Analyze historical forest fire data and identify relationships between environmental conditions and fire occurrence. ### 🤖 Machine Learning A supervised Machine Learning classification model is trained using historical forest fire observations. ### 🌐 Flask Web Application The trained model is integrated into a Flask web application for real-time predictions. ### 🖥️ Interactive User Interface Users can enter environmental values through a simple web interface and receiv …