Evaluation Modelling of Asteroids’ Hazardousness using ChaosNet

Modern Computational Fields including Machine Learning, Artificial Intelligence, Data Science, Internet of Things, and many others have emerged in response to recent technological advancements. The human race benefits greatly from these fields. Artificial Intelligence led to the innovations of a lot of Artificial Neural Networks. In this work, we are making use of one such Artificial Neural Network, namely ChaosNet, which is build on the Chaotic Dynamics shown by the Human Brain. It is made of unidimensional Generalized Luroth Series. The work encompasses around predicting Hazardousness of Asteroids. Numerous Asteroids are present in the solar space. Many have their course of path towards our Earth. Though, very few of them are hazardous, while many are non hazardous. The non hazardous ones gets completely burned up as they enter our atmosphere. In the other hand, the hazardous ones pose a great threat to mankind. Making use of ChaosNet, we would predict the hazardousness of any Asteroid to a higher accuracy than the traditional Classifiers. To do so, we have trained a Machine Learning Model making use of a recent dataset of Asteroids from the National Aeronautics and Space Administration.