Meteor Shower Scale Prediction Using Random Forest Classification

Abstract

With the development of science and technology, the aerospace industry also has been developing rapidly. At the same time, meteor showers from the universe become one of the severest threats to the increasing numbers of aero crafts in the outer space. With the advancement of computer science, we have been able to employ big data to analyze and predifct the scale of meteor showers, so as to reduce the possibility of meteor objects hitting spacecraft and provide a strong guarantee for aerospace security. The Random Forest Classification, a kind of machine learning algorithm, is used to analyze meteor showers that once visited the earth to explore the principle of meteoroid cycles and predict the scale of meteor showers that will enter the Earth. The confusion matrix and accuracy rate will be used to evaluate the performance of the machine learning model.