Comparison of Forest Fire Prediction System using Machine Learning Alogrithms

Fires in the forest are Uncontrolled flames, which gravely affect both normal and social resources, are one of the greatest harmful natural tragedies to the situation. The suggested approach makes advantage of a number of advancements, including machine learning techniques, which have a high probability of accurately representing the state of the forest ecosystem. Based on the strategy, we may be able to pinpoint the days that provide a substantial danger of forest fires and focus extra attention on forest fire prevention for forest guards. Forecasting future flames is part of the management of forest fires. It is crucial to the distribution of resources, the prevention of damage, and the pursuit of recovery. Using machine learning, this system is actively analyzing ways for predicting forest fires. We introduce a brand-new support vector machine-based forest fire risk prediction system. A forest's level of fire threat is predicted by the algorithm based on historical weather patterns and data. The algorithm's implementation makes use of the available data to correctly forecast the risk of a fire.