{"paper":{"title":"Predicting Coronal Mass Ejections transit times to Earth with neural network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.SR","authors_text":"B. Vr\\v{s}nak, D. Sudar, M. Dumbovi\\'c","submitted_at":"2015-11-24T09:26:46Z","abstract_excerpt":"Predicting transit times of Coronal Mass Ejections (CMEs) from their initial parameters is a very important subject, not only from the scientific perspective, but also because CMEs represent a hazard for human technology. We used a neural network to analyse transit times for 153 events with only two input parameters: initial velocity of the CME, $v$, and Central Meridian Distance, CMD, of its associated flare. We found that transit time dependence on $v$ is showing a typical drag-like pattern in the solar wind. The results show that the speed at which acceleration by drag changes to decelerati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.07620","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}