<ul data-eligibleForWebStory="false"><li>Accurate identification of meteoroid streams is crucial for understanding their origins and evolution, especially for missions like ESA's LUMIO that rely on meteor shower observations.</li><li>This study assesses the performance of the HDBSCAN unsupervised clustering algorithm in identifying meteoroid streams and compares it with the traditional CAMS look-up table method.</li><li>Using three different feature vectors, HDBSCAN successfully identifies meteoroid streams, with 39 streams confirmed using the GEO vector and 30 using the ORBIT vector.</li><li>HDBSCAN, while requiring careful parameter selection, outperformed the CAMS method in statistical coherence, showing potential as an effective alternative for meteoroid stream identification.</li></ul>

Meteoroid stream identification with HDBSCAN unsupervised clustering algorithm

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