Statistical Analyses and Deep Learning on Seismo-Ionospheric Precursors of the TEC Associated with the 21 September 1999 M7.3 Chi-Chi Earthquake

YUN-CHENG WEN; Jann-Yenq LIU; CHIYEN LIN

講演情報

[E] ポスター発表

セッション記号 M (領域外・複数領域) » M-IS ジョイント

[M-IS10] Interdisciplinary studies on pre-earthquake processes

2022年5月30日(月) 11:00 〜 13:00 オンラインポスターZoom会場 (31) (Ch.31)

コンビーナ:服部克巳(千葉大学大学院理学研究科)、コンビーナ:劉正彦(国立中央大学太空科学研究所)、Ouzounov Dimitar(Center of Excellence in Earth Systems Modeling & Observations (CEESMO) , Schmid College of Science & Technology Chapman University, Orange, California, USA)、コンビーナ:Huang Qinghua(Peking University)、座長:服部克巳(千葉大学大学院理学研究科)、Ouzounov Dimitar(Center of Excellence in Earth Systems Modeling & Observations (CEESMO) , Schmid College of Science & Technology Chapman University, Orange, California, USA)、劉正彦(国立中央大学太空科学研究所)、韓鵬(南方科技大学)

11:00 〜 13:00

[MIS10-P07] Statistical Analyses and Deep Learning on Seismo-Ionospheric Precursors of the TEC Associated with the 21 September 1999 M7.3 Chi-Chi Earthquake

*YUN-CHENG WEN¹、Jann-Yenq LIU²、CHIYEN LIN² (1.Department of Space Science and Engineering, National Central University, Taiwan、2.Center for Astronautical Physics and Engineering, National Central University, Taiwan)

キーワード：deep learning, earthquake, total electron content

The global ionosphere map of total electron content (TEC) is used to examine the characteristics of anomalies before the 21 September 1999 M7.3 Chi-Chi earthquake and M5.0 earthquakes in Taiwan during 2000-2021. The statical analysis finds the characteristics the polarity, duration, lead time, etc. of the TEC anomaly. The characteristics is then adopted by a deep learning method to construct a neural network, which will find possible coming large earthquakes. Meanwhile, a spatial analysis of TEC anomalies will be applied to confirm the possible coming large earthquake.