The experiment project for predicting the burned area of the forest fires specifically in the northeast region of Portugal, based on the spatial, temporal and weather variables where the fire is spotted using deep learning.

Forest fires are a significant threat to the environment, wildlife, and human lives

This project focuses on predicting the burned area of forest fires using Long Short-Term Memory (LSTM) neural networks. The LSTM model is trained on historical data to forecast the extent of forest fire damage based on various environmental and meteorological factors.

This project predicts forest fires in Algeria using machine learning models . The dataset includes various meteorological and environmental features such as temperature, humidity, and wind speed. The app cleans the data and builds models to predict the likelihood of forest fires based on historical data and environmental conditions.

Forest Fire Prediction using multiple Regression Models and Flask