Forest Fire Prediction based on Climate change Using Hybrid Optimized K-Means Clustering Algorithm

Today’s current era climate change is the undefendable biggest challenge. Every year the global temperature also changing dramatically. Due to climate change some of the natural calamities also happening frequently. In the year 2020 is predicted and recorded as a extreme globe hottest year of the world. This is happening of various reasoning such as assaults of social awareness, destroying of forest, pollution, factory wastage, etc., To identify and detect the climate change, various types of machine learning introduced. This research paper used hybrid machine learning algorithm, with optimization Techniques with the help of support vector machine. SVM can predict the possibility of fire forest due to climate change. After prediction of possibility, with the help of K-Means clustering algorithm can cluster the severity of the forest fire. Based on that, whether men can take the proper decision and prevention and also give the suggestion to avoid all disasters from the forest fire due to climate change. The performance of the algorithm is measured with the help of accuracy, precision and recall and produced high accuracy for the proposed method.