Identifying Earth-impacting asteroids using an artificial neural network
John D. Hefele, Francesco Bortolussi, Simon Portegies Zwart
Abstract
By means of a fully connected artificial neural network, we identified asteroids with the potential to impact Earth. The resulting instrument, named the Hazardous Object Identifier (HOI), was trained on the basis of an artificial set of known impactors which were generated by launching objects from Earth’s surface and integrating them backward in time. HOI was able to identify 95.25% of the known impactors simulated that were present in the test set as potential impactors. In addition, HOI was able to identify 90.99% of the potentially hazardous objects identified by NASA, without being trained on them directly.
Topics & Concepts
AsteroidArtificial neural networkSet (abstract data type)Artificial intelligenceIdentifierPhysicsBasis (linear algebra)Object (grammar)Pattern recognition (psychology)Test setData setDeep neural networksComputer visionAstrophysicsObject detectionComputer scienceAstro and Planetary SciencePlanetary Science and ExplorationSpace Science and Extraterrestrial Life