NEAs classification
THE CHALLENGE: Near Earth Objects Machine Learning
Solar System
For this challenge, we invite you to become "virtual contributors" to the Asteroid Grand Challenge and develop a hypothetical method, concept note or simple prototype that demonstrates how Machine Learning could be used to help us avoid the same fate as the dinosaurs.
Explanation
we wanted to detect potentially hazardous asteroids from the NEAs using machine learning techniques, so we used a specific learning algorithm (K-mean algorithm) . The input will be the 1696 known PHAs, we will use 2 clusters centroids.
The features used in the learning process:
- H:absolute magnitude.
- q:perihelion distance.
- Q:aphelion distance.
- Node:longitude of ascending node.
- Orbit arch.
- MOID.
After the learning process the system will be able to classify any newly observed asteroid as PHA or not.
Resources Used
