Classification of Natural Disasters Using Decision Tree Techniques

Abstract

The result of a natural hazard is a natural disaster. Earthquakes, landslides, tsunamis, and volcanoes are all natural disasters that cause economic, environmental, and human damage. The need of the hour is to predict such geological calamities. Furthermore, predicting these calamities is a complicated process that is influenced by a variety of physical and environmental factors. These natural risks can also be predicted using machine learning approaches. This proposed approach is primarily concerned with predicting loss owing to the impacted region. The system was created with the help of well-known classifiers like Decision Tree and Chai Square Technique based feature selection. In comparison to previous classifiers, our proposed classification method produces superior results. The afflicted data set is used to categories, and then the classifiers are compared to determine the disaster’s accuracy.