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DETECTION AND IDENTIFICATION OF NON-PERIODIC VARIATIONS OF COSMIC RAYS BASED ON PACKET DECOMPOSITION AND DEEP LEARNINGстатья Краткое сообщение
- Авторы: Mandrikova O.V., Dmitriev A.V., Mandrikova B.S.
- Сборник: Proceedings of the 18th Annual Meeting of the Asia Oceania Geosciences Society
- Год издания: 2021
- Номер статьи: ST06-A003
- DOI: 10.1142/9789811260100_0065
- Аннотация: Solar, galactic and magnetospheric energetic particles can create a serious radiation danger during space activities and affect astronauts and equipment, up to and including loss. Anomalous changes in the dynamics of cosmic rays occur during periods of nonstationary solar phenomena and heliospheric disturbances. At the moment, the problemof identifying and forecasting anomalies in cosmic rays is open. We propose an automated method for detecting and identifying non-periodic variations in cosmic rays, based on acombination of nonlinear adaptive schemes and deep learning. The Autoencoder paradigm and orthogonal package decompositions are used. The effectiveness of the method is confirmed by numerical calculations using data from neutron monitors of a network of ground stations.
- Добавил в систему: Дмитриев Алексей Владимирович