hazardous-asteroid-classification
Explainable Hazardous Asteroid Classification Using Graphs Neural Networks
https://github.com/baimamboukar/hazardous-asteroid-classification
Science Score: 54.0%
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Explainable Hazardous Asteroid Classification Using Graphs Neural Networks
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Metadata Files
README.md
This repository implements a Graphical Neural Networks and its variants (Graph Attention Networks and GraphSAGE) models to classifiy potentially hazardous asteroids on the NASA Jet Propulsion Lab's Small Body Datasets.
$\text{●•Authors}$
| $\text{Baimam Boukar Jean Jacques}$ |
| Carnegie Mellon University Africa |
|
|
|
●• $\text{Dataset Description}$
Our dataset, the Asteroid Dataset, is from NASA's Jet Propulsion Laboratory (JPL). It contains over 950,000 records, sourced from the official Small-Body Database by the NASA Jet Propulsion Lab. It was originally preprocessed by a NASA Astronomy and Astrophysics Researcher.
The preprocessed version is publicly available, and licensed under OpenData Commons Open Database License (ODbL) v1.0 by a JPL-authored document sponsored by NASA under Contract NAS7-030010.
The dataset contains detailed information on thousands of asteroids. Its main attributes include orbital eccentricity, semimajor axis,perihelion distance, absolute magnitude, diameter, and the Near-Earth Object (NEO) and Potentially Hazardous Asteroid (PHA) flags.
●• $\text{Methodology}$
●• $\text{Reproduction Steps}$
●• $\text{Cite This Paper}$
bibtex
@software{baimamboukar_2025,
author = {Baimam Boukar Jean Jacques},
month = apr,
title = {{Explainable Deep Learning Based Potentially Hazardous Asteroids Classification Using Graph Neural Networks}},
url = {https://github.com/baimamboukar/hazardous-asteroid-classification},
version = {1.0},
year = {2025}
}
Owner
- Name: BAIMAM BOUKAR JEAN JACQUES
- Login: baimamboukar
- Kind: user
- Location: Yaoundé
- Website: baimamboukar.medium.com
- Twitter: baimamjj
- Repositories: 13
- Profile: https://github.com/baimamboukar
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Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Baimam Boukar Jean Jacques" title: "Explainable Deep Learning Based Potentially Hazardous Asteroids Classification" version: 1.0 date-released: 2025-04-22 url: "https://github.com/baimamboukar/hazardous-asteroid-classification"
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