Forecast of global ionospheric TEC using an improved transformer model

Wu, Xuequn; Fan, Cihang; Tang, Jun; Cheng, Yuesong

doi:10.1016/j.asr.2024.02.003

Advances in Space Research

2024

DOI: 10.1016/j.asr.2024.02.003

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Forecast of global ionospheric TEC using an improved transformer model

Xuequn Wu,

Cihang Fan,

Jun Tang

et al.

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2024

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MaxEnt SeismoSense Model: Ionospheric Earthquake Anomaly Detection Based on the Maximum Entropy Principle

Wang,

Li,

Chen

et al. 2024

Atmosphere

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In our exploration, we aimed at identifying seismic anomalies using limited ionospheric data for earthquake forecasting and we meticulously compiled datasets under conditions of minimal geomagnetic disturbance. Our systematic evaluation affirmed the ITransformer as a potent tool for the feature extraction of ionospheric data, standing out within the domain of transformer-based time series prediction models. We integrated the maximum entropy principle to fully leverage the available information, while minimizing the influence of presuppositions on our predictions. This led to the creation of the MaxEnt SeismoSense Model, a novel composite model that combines the strengths of the transformer architecture with the maximum entropy principle to improve prediction accuracy. The application of this model demonstrated a proficient capability to detect seismic disturbances in the ionosphere, showcasing an improvement in both recall rate and accuracy to 71% and 69%, respectively, when compared to conventional baseline models. This indicates that the combined use of transformer technology and the maximum entropy principle could allow pre-seismic anomalies in the ionosphere to be sensed more efficiently and could offer a more reliable and precise approach to earthquake prediction.

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MaxEnt SeismoSense Model: Ionospheric Earthquake Anomaly Detection Based on the Maximum Entropy Principle

Wang,

Li,

Chen

et al. 2024

Atmosphere

View full text Add to dashboard Cite

show abstract

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Forecast of global ionospheric TEC using an improved transformer model

Cited by 1 publication

References 18 publications

MaxEnt SeismoSense Model: Ionospheric Earthquake Anomaly Detection Based on the Maximum Entropy Principle

MaxEnt SeismoSense Model: Ionospheric Earthquake Anomaly Detection Based on the Maximum Entropy Principle

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