Method for detecting anomalies in geomagnetic field variations based on artificial neural network
The paper proposes a method for anomaly detection in geomagnetic data based on the classical autoencoder architecture. The training data consisted of daily variations in the geomagnetic field on quiet days for 2020, 2021, and 2022, collected from the Ak-Suu base station of the geomagnetic monitori...
Saved in:
Main Author: | Imashev, Sanjar A. |
---|---|
Format: | Article |
Language: | English |
Published: |
Дальневосточного отделения Российской академии наук, Южно-Сахалинск, Федеральное государственное бюджетное учреждение науки Институт морской геологии и геофизики
2024-12-01
|
Series: | Геосистемы переходных зон |
Subjects: | |
Online Access: | http://journal.imgg.ru/web/full/f2024-4-6.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Evaluation of Variational Autoencoder in Credit Card Anomaly Detection
by: Faleh Alshameri, et al.
Published: (2024-09-01) -
Anomaly detection in multidimensional time series for water injection pump operations based on LSTMA-AE and mechanism constraints
by: Mei Wang, et al.
Published: (2025-01-01) -
Prompt Penetration Electric Fields and Ionospheric Effects of Major Geomagnetic Storms on Low Latitude Stations.
by: Talemwa, Gorretti
Published: (2025) -
Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment
by: Praveen Vijai, et al.
Published: (2025-03-01) -
The Probability of the May 2024 Geomagnetic Superstorm
by: S. Elvidge, et al.
Published: (2025-01-01)