Enhancing Geomagnetic Disturbance Predictions with Neural Networks: A Case Study on K-Index Classification

Enhancing Geomagnetic Disturbance Predictions with Neural Networks: A Case Study on K-Index Classification

To explore the application of neural networks for estimating geomagnetic field disturbances, this study pays particular attention to K-index classification. The primary goal is to develop a robust and efficient method for classifying different levels of geomagnetic activity using neural networks. Ou...

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Bibliographic Details
Main Authors: Aizhan Altaibek, Beibit Zhumabayev, Aiganym Sarsembayeva, Marat Nurtas, Diana Zakir
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Atmosphere
Subjects:
geomagnetic field
geomagnetic disturbances
neural networks
K-index
Online Access:https://www.mdpi.com/2073-4433/16/3/267
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