Asteroid Detection using Machine Learning Algorithm

Abstract

My paper starts from the question many of us wonder ‘What if an Asteroid hit Earth? The answer depends on how big an asteroid is in terms of dimension- Let’s say an asteroid of baseball ground hits earth, which can completely erase a city. Most of the asteroids are detected by Satellites, Probes and telescopes with large aperture length. Mostly large Telescopes from earth are used for tracking main belt asteroid but what if it gets out of sight from researchers or Scientists; it might take away peoples life. In this paper, I introduced machine learning to detect the asteroid with more than 60 percent of efficiency. The famous Scientist Stephen Hawking wrote in his last book that ‘Asteroids are great threatened to the planets’. Machine learning being a one of the best predictive method without explicitly giving any external command. In this paper, I attempt to introduce new machine learning algorithm in the replacement of Astrometrica software with Pan-Starr Telescope real-time Fits file data which is located in Hawaii, USA.