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AnshulGupta-14/Algerian-Forest-Fire-Prediction

Domaine:

environment and energy

Type de record:

software
Créateur:
Ans
HĂ´te:
# 🔥 Forest Fire Detection System A comprehensive machine learning-based web application for predicting forest fire risks in Algeria using environmental factors such as temperature, humidity, wind conditions, and rainfall. ## 🌟 Features ### **ML-Powered Predictions** - **Binary Classification Model**: Advanced machine learning algorithm for accurate fire risk assessment - **Real-time Analysis**: Instant predictions based on environmental parameters - **Risk Level Classification**: FIRE and NO FIRE risk categories ### **Interactive Dashboard** - **Prediction History**: Track all your previous predictions with detailed analytics - **Data Visualization**: Beautiful charts showing temperature trends, Fire Weather Index patterns, and risk distribution - **Summary Statistics**: Total predictions, average FWI, highest/lowest FWI scores - **Responsive Design**: Works seamlessly on desktop, tablet, and mobile devices ### **User Experience** - **Smooth Navigation**: GSAP-powered smooth scrolling between dashboard sections - **Active Page Indicators**: Clear navigation showing current page - **Custom Scrollbars**: Beautiful, dark-themed scrollbars for better visibility - **Hover Effects**: Interactive elements with smooth transitions and animations ### **Data Management** - **Local Storage**: Secure storage of user prediction history - **Data Persistence**: Predictions saved locally for privacy and convenience - **Export Ready**: Structured data format for future analysis ## 🏗️ Project Structure ``` ML Project 1/ ├── Backend/ # Python Flask Backend │ ├── app.py # Main Flask application │ ├── src/ # Source code │ │ ├── logger.py # Logging configuration │ │ ├── exception.py # Custom exception handling │ │ ├── utils.py # Utility functions │ │ └── pipeline/ # ML pipeline │ │ ├── predict_pipeline.py # Prediction pipeline │ …

Visit

github.com

Tasks

text classification

Languages

Arabic, Algerian Spoken