Forest Fire Prediction using Machine Learning

Abstract

Abstract: Forest Fire Prediction is a key component of forest fire control. This is a major environmental problem that decreases resources such as water that causes global warming and water pollution. Fire Detection is a key element for controlling such incidents. Prediction of forest fire is expected to reduce the impact of forest fire in the future. It plays a major role in resource allocation, mitigation and recovery efforts. Forest fire prediction system is based on predictive modeling that predicts the fire on the basis of weather conditions that user provides as an input to the system. This project presents a description and analysis of forest fire prediction methods based on machine learning and discusses about a comparative study of different models for predicting forest fire such as Decision Tree Classifier, Random Forest Classifier .We use Flask framework to develop web application and imported the NumPy and Panda’s modules to access and perform operations on data sets. We have taken several data sets and train the system in order to predict the fire by taking Temperature, Oxygen, Humidity as parameters to the system.