Algerian Forest Fire Prediction

  • Project Overview:Algerian Forest Fire Prediction is a cutting-edge machine learning solution developed to forecast the occurrence of forest fires in various regions of Algeria. Utilizing state-of-the-art data analysis techniques, this project aims to provide accurate and timely predictions to help prevent and manage forest fires effectively.
  • Github URL: Project Link
  • Key Features:
    • Accurate prediction of forest fire occurrences based on various environmental factors.
    • Real-time monitoring and analysis of crucial environmental parameters.
    • User-friendly interface for easy access.
  • How it Works:

    This machine learning algorithm is trained on environmental data of Algerian forests, encompassing temperature, humidity, wind conditions, and historical fire incidents. By analyzing these factors, the system accurately predicts the likelihood of forest fires in different regions of Algeria.

  • Deployment:

    Algerian Forest Fire Prediction is deployed using Flask. Proper setup of a Flask environment and installation of essential dependencies are necessary before deploying the application.